15 Data Science jobs in Australia

Machine Learning Scientist, International Machine Learning

Melbourne, Victoria Amazon

Posted 5 days ago

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Job Description

Description
Amazon has a rare opportunity for a talented Machine Learning Scientist to join an international team of ML experts changing the way our customers experience the everything store.
At Amazon's International Machine Learning team, we partner with businesses across the Amazon ecosystem to drive innovation and deliver exceptional experiences for customers around the globe. Our team works on large-scale, high-impact projects that leverage the latest advancements in machine learning and artificial intelligence.
As part of Amazon's Research and Development organization, you will have the opportunity to push the boundaries of applied science and deploy solutions that directly benefit millions of Amazon customers worldwide. Whether you are exploring the frontiers of generative AI, developing next-generation recommender systems, or optimizing agentic workflows, your work at Amazon has the power to truly change the world. Join us in this exciting journey as we redefine the present and the future of innovative applied science.
* You will take on complex problems, work on solutions that either leverage or extend existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking.
* In addition to coming up with novel solutions and building prototypes, you will deliver these to production in customer facing applications, in partnership with product and development teams.
* You will publish papers internally and externally, contributing to advancing knowledge in the field of applied machine learning and generative AI.
Key job responsibilities
- You will take on complex problems, work on solutions that either leverage or extend existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking.
- In addition to coming up with novel solutions and building prototypes, you will deliver these to production in customer facing applications, in partnership with product and development teams.
- You will publish papers internally and externally, contributing to advancing knowledge in the field of applied machine learning and generative AI.
About the team
Our team is composed of scientists with PhDs, with a strong publication profile and an appetite to see the impact of innovation on real-world systems at scale.
Basic Qualifications
- PhD in computer science, machine learning, engineering, or related fields
- Experience with programming languages such as Python, Java, C+- Experience in solving business problems through machine learning, data mining and statistical algorithms
- Experience researching, developing and implementing deep learning algorithms
Preferred Qualifications
- 3+ years of building machine learning models or developing algorithms for business application experience
- Strong publication record in top-tier peer-reviewed machine learning, natural language processing, or information retrieval conferences, e.g., NeurIPS, ICML, ICLR, ACL, KDD, AISTATS
Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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Machine Learning Engineer

2000 Sydney, New South Wales Salient Group

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Overview

Machine Learning Engineer position at Salient Group, Sydney (Hybrid Working) in FinTech. Role involves end-to-end machine learning initiatives from data ingestion and preparation to model development, deployment, and monitoring in production. You will work with technology, product, and operations teams to design robust ML solutions and integrate them into core platforms.

Responsibilities
  • Data Exploration & Preparation: Gather, clean, and analyse datasets from multiple internal and external sources; develop and maintain scalable data pipelines using AWS services (Glue, Athena, Redshift); build, train, and optimise ML models in AWS SageMaker for use cases such as anomaly detection, predictive modelling, and data quality improvement; perform feature engineering, selection, and rigorous evaluation of models.
  • Deployment & MLOps: Deploy models to production using SageMaker endpoints or other AWS deployment mechanisms; implement monitoring, alerting, and retraining workflows to ensure continued model performance; manage model versioning, governance, and documentation; partner with business and product teams to define ML use cases and success metrics; translate complex technical outputs into clear, actionable business insights; present findings to both technical and non-technical stakeholders.
Required Skills & Experience
  • Proven experience with the AWS ML stack: SageMaker, Glue, Athena, Redshift, Kinesis, Lambda, S3.
  • Strong data science background: statistics, ML algorithms, feature engineering, and model evaluation.
  • Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL.
  • Experience with MLOps practices: CI/CD pipelines for ML, model monitoring, and retraining strategies.
  • Understanding of data governance, security, and compliance requirements (experience in financial services is a plus).
  • Excellent problem-solving skills, ability to work independently in a fast-paced environment.
  • Experience with financial, capital markets, or operational datasets.
  • Knowledge of AWS Bedrock or other generative AI tools.
  • Exposure to time-series forecasting, anomaly detection, or fraud detection.
  • Familiarity with Infrastructure-as-Code (Terraform, CloudFormation).
  • Experience with emerging AI frameworks and agentic AI systems (e.g., RAG, LangGraph, CrewAI, or other agent-based orchestration frameworks).
Additional Information
  • Location: Sydney, NSW (Hybrid)
  • Application contact:
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Machine Learning Engineer

2000 Sydney, New South Wales Rokt

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1 week ago Be among the first 25 applicants

This range is provided by Rokt. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

A$130,000.00/yr - A$85,000.00/yr

We are Rokt, a hyper-growth ecommerce leader. Rokt is the global leader in ecommerce, unlocking real-time relevance in the moment that matters most. Rokt's AI Brain and ecommerce Network powers billions of transactions connecting hundreds of millions of customers, and is trusted to do this by the world's leading companies.

We are a team of builders helping smart businesses find innovative ways to meet customer needs and generate incremental revenue. Leading companies drive 10-50% of additional revenue—and often all their profits—from the extra products or services they sell. This economic edge unleashes a world of possibilities for growth and innovation.

At Rokt, we practice transparency in career paths and compensation. At Rokt, we believe in transparency, which is why we have a well-defined career ladder with transparent compensation and clear career paths based on competency and ability. Rokt'stars constantly strive to raise the bar, pushing the envelope of what is possible.

We are looking for a Machine Learning Engineer

A fixed annual salary of $130 000 - 185,000 (including superannuation,) an employee equity plan grant, and world-class benefits.

Equity grants are issued in good faith, subject to company policies, board approval, and individual eligibility.

About The Role

If you're nearing the completion of your PhD in Machine Learning, have recently graduated, or bring equivalent hands-on experience, this is your opportunity to launch a high-impact career in applied AI. As an ML Engineer on our Research & Modelling team, you'll translate cutting-edge academic insights into scalable ML products that shape user experiences across more than 6 billion transactions and 400 million customers globally.

Working alongside world-class engineers and product teams, you'll design, train, and productionize proprietary models that solve real business challenges—ranging from click-through rate prediction and recommendation systems to creative content generation using large language models (LLMs).

If you're driven by bold ideas, inspired by solving hard problems, and excited to push the boundaries of what's possible with machine learning, we'd love to hear from you.

Requirements

What You'll Do

  • Frame & Solve ML Problems: Partner with colleagues to understand priorities, define machine learning problems, and design solutions that drive business outcomes.
  • Build & Operationalize ML Systems: Develop and productionize end-to-end ML pipelines—including data processing, orchestration, modeling, and continuous deployment—ensuring reliability and scalability.
  • Research & Experiment: Stay current with emerging ML technologies. Prototype new models and validate them through experimentation, both offline and online (e.g., A/B testing).
  • Accelerate Development with AI: Leverage AI-driven tools and automation to implement clean, maintainable and well-tested code - allowing you to focus on creative problem-solving and quality.
  • Collaborate & Innovate: Work closely with diverse teams—to build cohesive ML solutions. Share knowledge through talks, brown bags, and mentoring
  • Drive Business Impact: Build capabilities that create personalized experiences and unlock millions in incremental revenue for the world's leading ecommerce brands.

Who You Are

  • AI-Driven & Curious: You're an AI enthusiast who stays ahead of the curve—whether through a recent PhD in Machine Learning or hands-on experience with advanced architectures like MOEs, MMOE, or xDeepFM
  • ML Domain Expertise: You have deep knowledge in one or more of: deep learning, Bayesian methods, reinforcement learning, econometrics, NLP or gradient boosting techniques.
  • Technically Versatile: You bring a solid grasp of software engineering, system design, and cloud architecture, with bonus points for production experience in Kubernetes, TFX, Kubeflow, or Feature Stores.
  • Creative Problem Solver: You break down complex challenges using first principles thinking, creativity, and a strong analytical foundation across both ML and engineering domains.
  • Entrepreneurial Mindset: You take ownership of outcomes, move fast with confidence, and aren't afraid to navigate ambiguity—figuring things out independently when needed.
  • Collaborative Team Player: You communicate clearly and work well with cross-functional teams. You value feedback, share ideas openly, and help others succeed.
  • Driven & Results-Oriented: You set the bar high, consistently deliver quality, and care deeply about the real-world impact of your work—on both customers and business outcomes.

Benefits

Why Join Rokt

  • Build the Future of AI in Ecommerce: Be at the forefront of AI-driven transformation in a company that's pioneering how brands engage customers in the "moment that matters" during online transactions.
  • Hyper-Growth = Fast Progression: Rokt is a rapidly growing tech leader, which means huge opportunities for your career advancement, learning, and taking on bigger responsibilities quickly.
  • Culture of Builders: Work with a smart, humble, and bold team that shares a "builder" DNA - we love to innovate, take risks, and turn ambitious ideas into tangible results. We win as a team and learn from every experiment.
  • Ownership & Impact: Every Rokt'star (employee) has a voice and real equity in the company. You'll have autonomy to make decisions, drive projects, and see the direct impact of your work on millions of users.
  • World-Class Benefits & Support: Join a people-first culture with transparent career paths, continuous development (LevelUp training, mentorship), and great perks (equity grants, catered lunches, global offices, and more) that empower you to do your best work.

About The Benefits

We leverage best-in-class technology and market-leading innovation in AI and ML, with all of that being underlined by building and maintaining a fantastic and inclusive culture where people can be their authentic selves, and offering a great list of perks and benefits to go with it:

  • Become a shareholder. Every Rokt'star gets equity in the company
  • Enjoy catered lunch every day and healthy snacks in the office. Plus join the gym on us!
  • Extra leave (bonus annual leave, sabbatical leave etc.)
  • Work with the greatest talent in town
  • See the world! We have offices in New York, Seattle, Sydney, Tokyo and London

We believe we're better together. We love spending time together and are in the office most days (teams are in the office 4 days per week).

We at Rokt choose to create a company that is as diverse and inclusive as the world we live in by attracting, growing & keeping the best talent. Equal employment opportunities are available to all applicants without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

If this sounds like a role you'd enjoy, apply here, and you'll hear from our recruiting team.

Note: The first stage of the recruitment process for this role is to complete a 15-minute online aptitude test as well as an employee personality profile assessment, which will be sent out to your application email. Successful candidates will be contacted to discuss the next steps.Seniority level
  • Seniority levelAssociate
Employment type
  • Employment typeFull-time
Job function
  • IndustriesAdvertising Services, Technology, Information and Internet, and Software Development

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Machine Learning Operations Engineer

2000 Sydney, New South Wales Virtusa

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Overview

Machine Learning Operations Engineer role at Virtusa. Join to apply for this position.

Responsibilities
  • Should have a solid understanding of CI/CD and MLOps best practices.
  • Designing and implementing solutions on the Amazon Web Services (AWS) ecosystem.
  • Strong understanding of AWS and proficiency in Python for scripting and ML model integration.
  • Hands-on experience with Docker, GitHub Actions, and Apache Airflow.
  • Familiarity with AWS CloudFormation, AWS Glue, and AWS Lambda.
  • Experience deploying ML models using Amazon SageMaker.
Qualifications
  • Experience with AWS services and Python for ML tasks.
  • Proficiency in Docker, GitHub Actions, and Apache Airflow.
  • Familiarity with AWS CloudFormation, AWS Glue, and AWS Lambda.
  • Experience deploying ML models on SageMaker or similar platforms.
Job Details
  • Seniority level: Mid-Senior level
  • Employment type: Full-time
  • Job function: Engineering and Information Technology
  • Industries: IT Services and IT Consulting

Note: This posting has been cleaned to remove unrelated content and present the core responsibilities and requirements for the role.

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Senior machine learning engineer

Adelaide, South Australia Rheinmetall

Posted 3 days ago

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full time

What We Are Looking For

About the Team

This position will be a key member of the Electronics Solutions team located in Edinburgh, SA which provides engineering services for the design and build of systems to manage large quantities of imagery, and apply deep learning through convolutional neural networks and other machine learning models to augment imagery analysis.

About The Role

Under the supervision of the Technical Lead, undertake Machine Learning design and development activities as part of the larger engineering project team. You will be working with Researchers and Data Engineers at DST, this role includes utilising and adapting open-source machine learning libraries to assist with automation of computer vision tasks for Analysts.

What Qualifications You Should Have

What are we looking for?

Rheinmetall seeks applicants who exemplify our Company’s values of Safety, Partnering, Openness, Respect and Trust (SPORT) . This creates a workplace environment where employees value each other, live up to their promises and communicate openly.

The experience and skillset best suited to this role includes:


  • Experience in development of Machine Learning systems;
  • Knowledge in Machine Learning and/or AI;
  • Good understanding of best practice DevOps;
  • Experience with the software development lifecycle (CI/CD process);
  • Knowledge in software environments such as C++, Python, JAVA, JavaScript. RestFul interfaces, Docker;
  • Imagery Analysis experience;
  • Knowledge in Object Orientated design methodologies and SQL;
  • Exposure to developing applications using Linux OS and API’s;
  • Ability to travel internationally and interstate, when required; and
  • A NV1 Australian Government Security Clearance (Australian Citizenship required).


What We Offer You


  • Long weekends every second week with a 9 day fortnight;
  • Individualised Flexible Working Arrangements;
  • Access to exclusive employee discounts with over 500 retailers to support cost of living;
  • Market leading parental leave and loyalty leave accrual for every year of service;
  • We are proud to be an Endorsed Employer for All Women with WORK180.


CONTACT INFORMATION

RDA Talent Acquisition Team



Applications will close on 15th of November 2025.

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2026 Applied Science Intern (Machine Learning, Recommender Systems), International Machine Learning

Melbourne, Victoria Amazon

Posted 5 days ago

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Description
Are you excited about leveraging state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, Natural Language Processing algorithms on large datasets to solve real-world problems?
As an Applied Scientist Intern, you will based in Amazon's Melbourne office working in a fast-paced, cross-disciplinary team of experienced R&D scientists. You will take on complex problems, work on solutions that leverage existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even deliver these to production in customer facing products.
Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2026.
The successful intern is required to be based in Melbourne and relocation allowance will be provided if you are based outside of Melbourne.
Key job responsibilities
- Develop novel solutions and build prototypes
- Work on complex problems in Machine Learning and Information Retrieval
- Contribute to research that could significantly impact Amazon operations
- Collaborate with a diverse team of experts in a fast-paced environment
- Collaborate with scientists on writing and submitting papers to top conferences, e.g. NeurIPS, ICML, KDD, SIGIR
- Present your research findings to both technical and non-technical audiences
Key Opportunities:
- Work in a team of ML scientists to solve recommender systems problems at the scale of Amazon
- Access to Amazon services and hardware
- Become a disruptor, innovator, and problem solver in the field of information retrieval and recommender systems
- Potentially deliver solutions to production in customer-facing applications
- Opportunities to be hired full-time after the internship
Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!
Basic Qualifications
- Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Mathematics, or related field, with specialization in Information Retrieval, Recommender Systems, or Machine Learning
- Strong programming skills, e.g. Python and DL frameworks
Preferred Qualifications
- Research experience in Deep Learning, Recommender Systems, Information Retrieval, or broader Machine Learning.
- Publications in top-tier conferences, e.g. NeurIPS, ICML, ICLR, KDD, SIGIR, RecSys
- Experience with handling large datasets and distributed computing, e.g. Spark
Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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Forward Deployed Machine Learning Engineer

2000 Sydney, New South Wales CloudFlare

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Forward Deployed Machine Learning Engineer

Hybrid

About Us

At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.

We realize people do not fit into neat boxes. We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills, and we are ready to help you do that. We cannot complete our mission without building a diverse and inclusive team. We hire the best people based on an evaluation of their potential and support them throughout their time at Cloudflare. Come join us!

Available Location: Sydney

About the Department

Emerging Technologies & Incubation (ETI) is where new and bold products are built and released within Cloudflare. Rather than being constrained by the structures which make Cloudflare a massively successful business, we are able to leverage them to deliver entirely new tools and products to our customers. Cloudflare’s edge and network make it possible to solve problems at massive scale and efficiency which would be impossible for almost any other organization.

About the Team

Workers AI is Cloudflare’s AI inference service, enabling customers to use a wide variety of AI models both within Cloudflare’s Workers development platform and via API. The Workers AI team owns the whole stack that powers the product, from front-end development all the way to low-level inference code. Accordingly we’re a team with a diverse array of technical skills, but everyone on the team is curious and passionate about the possibilities of generative AI.

What You’ll Do

Forward Deployed Machine Learning Engineers work closely with Cloudflare’s customers to help them bring their AI applications to life on Cloudflare Workers AI. This will involve all of the following:

  • Helping customers package and deploy models for Workers AI
  • Adding new open-source models to the Workers AI model catalog to support customer initiatives
  • Optimizing model deployment and performance
  • Deeply understand and debug customers’ generative AI applications
Qualifications
  • Experience deploying generative AI models using popular open source libraries and inference engines (transformers, vllm, sglang)
  • Comfortable with image generation pipelines including using diffusers library and comfyUI
  • Experience implementing and optimizing generative AI models in pytorch
  • Familiarity with popular application frameworks such as LangChain and Cloudflare agents
  • Experience working directly with customers to meet their requirements is essential
What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo

Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project

In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1

We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you’d like to be a part of? We’d love to hear from you!

This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.

Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer.

Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at or via mail at 101 Townsend St. San Francisco, CA 94107.

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About the latest Data science Jobs in Australia !

University biology and machine learning

3083 Bundoora, Victoria La Trobe University

Posted 14 days ago

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Job Description

full time

  • Position to be based at La Trobe Melbourne Campus.
  • An amount of $40,000 per annum for 3.5 years, fee relief additional, fortnightly stipend.

The Position

This prestigious La Trobe University scholarship, in partnership with the Australian Office of National Intelligence, will be awarded to an outstanding applicant interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning.

The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models to individualise tumour type, associated biomarkers and genomic characteristics to high precision. The resulting multipurpose machine learning workflows will lead to rapid precision diagnoses and effective individualized cancer care plans. Coding and user interface development skills will be developed.

This scholarship is open only to Australian citizens, Australian permanent residents, or New Zealand special category visa holders. The Expression of Interest will remain open until the positions are filled.

Benefits Of The Scholarship Include

  • a stipend scholarship for three and a half years, with a value of $40,000 per annum (pro-rata), to support your living costs.
  • a fee-relief scholarship for up to four years.
  • opportunities to work with La Trobe’s outstanding researchers in state-of-the-art laboratories and have access to our suite of professional development programs.
  • a collaborative project, including time spent with the Olivia Newton-John Cancer Research Institute and CSIRO.
  • opportunities to travel to conferences in Australia and overseas.

Eligibility Criteria

To be eligible to apply for this scholarship, applicants must:

  • be Australian citizens, Australian permanent residents, or New Zealand special category visa holders (strict requirement).
  • meet the entrance requirements for the Doctor of Philosophy.
  • should they be selected, agree to be enrolled full-time and undertaking their research at the La Trobe University Melbourne (Bundoora) campus.

In selecting successful applicants, we prioritise applications from candidates who:

  • have an outstanding record of prior performance.
  • have completed a Masters by Research or other significant body of research, such as an honours research thesis or lead authorship of a peer-reviewed publication, assessed at a La Trobe Masters by research standard of 75 or above.
  • have outstanding grounding in one or more relevant disciplines including cancer biology, cancer medicine, physics, chemistry, , engineering, machine learning / data science, coding.

How To Apply

This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information via email to :

  • current academic transcript including Masters / Honours grades (or note completion date).
  • a statement outlining:
  • their motivation and suitability for this opportunity;
  • their specific skills and experience and how these are relevant to the PhD project;
  • how this opportunity fits with their career plans.
  • a statement confirming that you are currently an Australian citizen, Australian permanent resident, or New Zealand special category visa holder.

Shortlisted applicants will be required to attend an interview and may be asked to participate in further evaluation activities.

The successful applicant will be required to have a working with children check (WWCC) prior to commencing the position, to be paid for by the applicant.

The University will carefully review and consider your expression of interest for this scholarship. Successful candidates will be invited to submit a full application for candidature and scholarship.

See Also

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Who To Contact For Further Information

Professor Paul Pigram,

Closing date for applications: Indefinite

Scholarship code: SRS-25030

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Research assistant / associate - machine learning

Newcastle, New South Wales American Nano Society

Posted 28 days ago

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Job Description

full time

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Salary

Research Assistant - £28,756 to £0,497 per annum

Research Associate 1,406 to 3,309 with progression to 0,927 per annum

Closing Date : 15th February 2022

The Role

This exciting Research Assistant/Associate position is for a Machine Learning expert who will join a multi-national European project. The candidate will become a member of the ICOS Research Group ( and work under the direction of Prof. N. Krasnogor and Dr E. Torelli.

During the project, you will have the opportunity to investigate, develop and apply machine learning techniques, in collaboration with consortium partners, to datasets derived from real-world experimental data.

You will have the opportunity to contribute towards data sets definition, federation and collection; data capture from instruments and experiments; data wrangling, etc. You will create deep learning tools for predicting experimental outcomes and process optimisation. You will have the opportunity to work on an integrated loop in which every round of machine learning prediction can be used to improve the experimental activities carried out by the consortium and hence gather more and better data for the next round of iterations.

You will work towards the milestones set out for Newcastle within this multi-national project. Furthermore, the researcher will keep excellent records of all computational experiments, procedures, protocols, workflows and outcomes, enabling reuse, interpretation by team members and delivery of project milestones. You will be responsible for reporting to the consortium and publishing the work (either as papers or software or both).

We are seeking a dedicated individual with demonstratable communication skills, a consummate team player with the ability to produce actionable machine learning workflows of a high quality at an experienced level. We are looking for a committed individual with exceptional talent. As part of our drive to build a stellar team, the final selection of short-listed candidates will involve (a) a pre-interview practical exercise, (b) a remote video interview, (c) a post-interview exercise and (d) a collection of at least 2 satisfactory reference letters. Shortlisted candidates who complete this process (whether successful or not will have an inconvenience expense paid). Candidates who are not prepared to fulfil steps (a, b, c & d) should not apply. Candidates close to completing their PhDs can apply.

This position is available on a full time, fixed term basis, to start immediately and is tenable for 24 months from the start date, or until the official project end date, whichever is soonest.

Relocation to the United Kingdom is not required and remote applicants are welcome to apply.

For any informal enquiries please contact Prof. Natalio Krasnogor, Professor of Computing Science and Synthetic Biology via email:

Key Accountabilities

Design, implement, test and debug the entire integrated machine learning workflow for the consortium Establish the data sets strategy for the consortium including data sets definitions, data capture, federation and collection architecture, data wrangling, etc. Utilise state-of-the-art machine learning toolkits to bootstrap the ML infrastructure and -if appropriate- create new toolkits for unmet challenges Development of repeatable computation protocols for the above demonstrating the successful operation of the consortium’s ML workflow, including regular software releases via a version control system Contribution to writing scientific papers and project reports Oral presentations at scientific meetings, workshops, conferences as well as business & consortium meetings The Person (Essential)

Knowledge, Skills And Experience

Demonstrable experience establishing machine learning infrastructures from data acquisition to actionable ML predictions Demonstrable experience with deep learning and other machine learning techniques Demonstrable experience with state-of-the-art ML software packages Demonstrable experience with cloud computing infrastructure for machine learning applications Demonstrable software engineering experience including version control Desirable

Demonstrable experience publishing in peer-reviewed outlets Demonstrable experience in laboratory automation Demonstrable experience applying ML to bioinformatics, chemoinformatics, nanotechnology or biotechnology Demonstrable experience working with scientists and engineers across different discipline Presentation of work at technical as well as more general stakeholders meetings Attributes and Behaviour

Excellent communication skills both oral and written (e.g software documentation, technical reports, papers, presentations, pitches, etc) Capacity for original thought and independent action Enthusiastic, hardworking and goal-setter Ability to interact with people from different disciplines and, while working as part of a team, drive machine learning infrastructure forward Punctual and generally dependable Qualifications

PhD awarded (essential) in computing science, engineering, mathematics or a very closely related discipline (Associate Level) Candidates must be able to spend time away from Newcastle visiting collaborators' labs and attending business meetings outside Newcastle, including international conferences and industrial partners The School/Institute holds a bronze Athena SWAN award in addition to the University’s silver award in recognition of our good employment practices for the advancement of gender equality. The University also holds the HR Excellence in Research award for our work to support the career development of our researchers, and is a member of the Euraxess initiative supporting researchers in Europe.

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains staff from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.

Requisition ID: 6341

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Machine Learning Engineer, Generative AI Innovation Center

Melbourne, Victoria Amazon

Posted 5 days ago

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Job Description

Description
The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As an SDE on our team, you will drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS's custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients.
Key job responsibilities
- Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
- LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
- Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
- Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions
A day in the life
AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You'll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
About the team
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
What if I don't meet all the requirements?
That's okay! We hire people who have a passion for learning and are curious. You will be supported in your career development here at AWS. You will have plenty of opportunities to build your technical, leadership, business and consulting skills. Your onboarding will set you up for success, including a combination of formal and informal training. You'll also have a chance to gain AWS certifications and access mentorship programs. You will learn from and collaborate with some of the brightest technical minds in the industry today.
Basic Qualifications
- 3+ years of non-internship professional software development experience
- 2+ years of Industry (non-internship) design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference)
- Hands-on experience with generative AI technology
Preferred Qualifications
- 2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- 1+ years of experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework
Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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