Expression of Interest - CommBank AI Labs Scholars, 6-month onsite AI internship

Who are we?

CommBank AI Labs are a globally recognised applied AI research team, combining academic rigour with real-world impact CommBank is ranked #1 Asia Pacific bank for AI maturity by the 2026 Evident AI Index (#4 globally) Partnerships with global leaders including Anthropic, AWS, Google, Microsoft and OpenAI Publishers of research at top-tier conferences while building real-world AI products that improve our customer experience and ways of working.

You are

A PhD researcher from a leading institution, driven to take your work beyond theory by applying cutting-edge research to meaningful problems, publishing at top venues, and building a globally distinctive research profile.

You’re motivated by depth, rigour, and impact and excited by the opportunity to see your research translated into real-world systems used at scale.

Together we can

Take a research idea from concept to publication and see it evolve into real-world products and experiences that can impact millions of customers.

Bring your ambition and we’ll help you grow, belong and shape what’s next in applied AI research.

Do work that matters

At CommBank AI Labs, we focus on research that delivers both academic contribution and applied impact, spanning agentic systems, LLM evaluation, causal machine learning, and responsible AI.

This program is designed for researchers who want to:

Produce high-quality, publishable work Work on complex, unstructured, real-world datasets Understand how research transitions into live products and customer experiences

Over six months in Sydney, you’ll work on a defined research problem — with a clear pathway to submission at a top-tier conference, and visibility into how your work could translate into production systems used at scale.

See yourself in our team

You’ll join a global network of AI scientists, decision scientists and engineers, working together to solve complex challenges through advanced analytics and machine learning.

You’ll be surrounded by people who are equally committed to research excellence, innovation, and real-world outcomes.

What makes this different A six-month onsite residency designed to enable meaningful research outcomes Access to large-scale, real-world datasets and problem spaces Opportunity to contribute to AI-driven products impacting millions of customers Highly competitive compensation and salary (AUD) aligned to global benchmarks Relocation support, including visa sponsorship and initial accommodation

Mentorship & research environment You’ll be supported by a diverse set of experienced AI practitioners, researchers and decision scientists across multiple disciplines with an unmatched wealth of expertise from global banking and AI research. You will work within a team led by CommBank’s Chief AI Scientist, renowned AI researcher Professor Mary-Anne Williams.

This creates a faculty-style environment, where your work is shaped by multiple perspectives, strengthening both the quality and impact of your research.

What you’ll work on - We’re particularly interested in researchers working on:

Agentic AI systems and multi-agent orchestration LLM evaluation, alignment, and AI safety Causal inference and counterfactual reasoning Responsible AI, fairness, and interpretability Applied AI for financial services (risk, fraud, decisioning)

We’re interested in hearing from people who: Are currently enrolled in a PhD or within 12 months post-submission Have a strong research track record in Machine Learning, AI, Statistics, Computer Science or related fields Have first-author publications or submissions at leading conferences (NeurIPS, ICML, ICLR, AISTATS, EMNLP, IJCAI or similar) Are motivated to apply research to complex, real-world problems Can be based in Sydney for the duration of the program

Job Description

About Global Quantitative Strategies (GQS)

GQS is the quantitative investment business unit of Citadel. Founded in 2012, GQS has grown rapidly to become one of Citadel’s core investment strategies and one of the top quantitative investment teams in the world. Collaborative teams of researchers, engineers, and traders build robust systems that operate at scale and apply advanced quantitative and machine learning techniques to identify investment opportunities.

Machine Learning Researchers at GQS develop and deploy models across a variety of asset classes. Their work spans deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, reinforcement learning, and methods for improving robustness in complex financial regimes.

Location

New York, Singapore

Required Skills and Qualifications:

• Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Physics, or a related quantitative field
• Proven ability to conduct innovative and impactful research focused on solving real-world problems
• Deep expertise in machine learning and deep learning, such as sequence modeling, large language models, or reinforcement learning
• Experience with modern training techniques such as pre-training, fine-tuning, reinforcement learning, or related optimization methods
• Expertise in Python and machine learning frameworks such as PyTorch or JAX
• Strong mathematical and statistical foundations
• Ability to design, implement, and optimize machine learning models for performance, scalability, and robustness
• Demonstrated interest in financial markets and a drive to apply machine learning techniques to model price formation, market behavior, and risk

We collect and use personal data in accordance with our Privacy Policy. We retain data on prospective candidates and may consider suitability for alternative opportunities at Citadel. For more information, see our Privacy Policy.

In accordance with applicable law, the base salary range for this role is $300,000 to $350,000.

In addition, the employee who fills this role will be eligible to participate in a discretionary incentive compensation program, as well as a wide array of benefit programs, such as medical and life insurance, retirement and tax-free savings plans, and access to other healthcare programs.

About Citadel

Citadel is one of the world’s leading alternative investment managers. We manage capital on behalf of many of the world’s preeminent private, public and nonprofit institutions. We seek the highest and best use of investor capital in order to deliver market leading results and contribute to broader economic growth. For over 30 years, Citadel has cultivated a culture of learning and collaboration among some of the most talented and accomplished investment professionals, researchers and engineers in the world. Our colleagues are empowered to test their ideas and develop commercial solutions that accelerate their growth and drive real impact.

We have roles across 4 locations:

Beijing, China

London, UK

San Francisco, US

Sydney, AU

Vienna, Austria

About the team

Canva Research's mission is to advance AI technology for Canva's Creative Operating System, making design accessible to everyone. Our team, established in June 2025, has rapidly grown across cities such as Sydney, London, Vienna, San Francisco, and Beijing. We focus on generative image, video, audio, agents, evaluations, on-device, and foundation models, transforming research breakthroughs into features that enhance Canva's platform.

About the role

As a Senior Research Engineer, you will be integral in transforming Canva Research's innovations into scalable products. Your role involves taking research prototypes in areas like generative models and agents, and developing them into technology that millions use for creative storytelling. We welcome candidates from various backgrounds, including generative model engineering, agent systems, evaluation infrastructure, or systems optimization. The key requirement is strong production ML engineering skills and the ability to judge when a product is ready to ship.

What you'll do

• Design systems to convert generative research into features, such as model serving and on-device deployment
• Evaluate systems for model selection and measure effectiveness
• Manage infrastructure for large-scale training, evaluation, and deployment
• Develop evaluations capturing real quality and user intent
• Collaborate with product teams to integrate research prototypes into Canva features
• Enhance and scale models for efficiency across distributed systems
• Work with cross-functional teams to create impactful solutions

You're likely a match if you have

• 5+ years of ML research or engineering experience with a proven track record in production
• Strong software engineering skills in Python for building scalable ML systems
• Hands-on experience in generative model training, agent architectures, or systems optimization
• Familiarity with large-scale distributed training and serving infrastructure
• Strong experimental skills and ability to translate research into scalable systems
• Excellent communication skills and ability to work collaboratively with research scientists
• Curiosity and awareness of industry trends and emerging technologies

Nice to have

• Knowledge of multimodal data or models
• Experience in designing evaluations for ML products
• Open-source contributions or publications in ML systems or multimodal research
• Experience with creative tools or design tooling

Locations: Hong Kong, Shanghai, Singapore, Sydney

Responsibilities -Designing, implementing and deploying trading algorithms -Researching high to mid frequency alphas -Exploring trading ideas by analyzing market data, market microstructure and alternate data for patterns -Creating tools to analyze data for patterns and developing data platforms -Contributing to libraries of analytical computations to support market data analysis and trading -Developing, augmenting and calibrating exchange simulators

Qualifications -A Bachelors, Masters or PhD degree in Mathematics, Statistics, Computer Science or equivalent STEM degree -Experience in quantitative trading is preferred but not a requirement -A strong background in mathematics and statistics -Proficiency in back-testing, simulation, and statistical techniques (auto-regression, auto-correlation and Principal Component Analysis) -Solid data-mining and analysis skills, including experience dealing with a large amount of data/tick data -Familiarity with signal generation and statistical models -Strong programming skills in Python or C++

The Michael Smith Laboratories (MSL) and the Department of Biochemistry & Molecular Biology (BMB) at the University of British Columbia (UBC) invite applications for a Canada Impact+ Emerging Leader in AI-based Protein Modeling and Design. This is a tenure-track appointment at the rank of Assistant Professor, jointly appointed in MSL and BMB, with an anticipated start date no later than July 1, 2027.

AI-driven protein design is one of the most rapidly advancing frontiers in science, with transformative potential in medicine, biotechnology, and the life sciences. We seek outstanding candidates with an innovative and impactful research program integrating deep learning and AI-driven approaches across the protein design pipeline. Research programs may leverage structure-based models, protein language models, generative AI, or novel hybrid approaches. Areas of interest include, but are not limited to, developing predictive and generative models for protein structure and function, advancing AI-enabled design-build-test-learn workflows, and creating new tools for the characterization and validation of engineered proteins. Example application areas include the design of protein binders with tailored binding specificity and affinity, protein conformational switches that sense and respond to their environment, de novo enzymes for applications in medicine and sustainability, and proteins that interact selectively with non-protein molecules (e.g. nucleic acids, carbohydrates, small molecules).

About the Canada Impact+ Emerging Leaders Program The Canada Impact+ Emerging Leaders program is a one-time initiative designed to support institutions in attracting internationally based Early Career Researchers to Canada. Emerging Leaders will receive research funding and institutional supports to advance transformative research in Canada's strategic priority areas, build partnerships across sectors and borders, and translate their research into applications and impacts that benefit Canadians and the world. Canada Impact+ Emerging Leaders are six-year positions, renewable once for an additional six years, intended for exceptional emerging scholars who have the potential to lead in their fields. Applicants must be an early career researcher and be eligible to hold a full-time, tenure-stream appointment at the rank of Assistant Professor at UBC.

Under the Canada Impact+ Emerging Leaders program, nominees must be working and residing outside Canada when the Eddie Goldenberg Research Chairs of Canada award (https://www.canada.ca/en/impact-plus-chairs.html is formally accepted. For this specific award, the acceptance date was July 1, 2026. Applicants may apply regardless of their current location; however, candidates selected for nomination must meet this eligibility requirement on the award acceptance date in order to proceed. Expatriate Canadians wishing to relocate to Canada are welcome to apply.

For more details and how to apply, please refer to UBC Faculty Careers website: https://ubc.wd10.myworkdayjobs.com/en-US/ubcfacultyjobs/job/UBC-Vancouver-Campus---Vancouver-BC-Canada/Canada-Impact--Emerging-Leader-in-AI-based-Protein-Modeling-and-Design_JR26070

Locations: London, United Kingdom; New York, NY, United States; Singapore

Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development teams in New York, London, and Singapore. Algorithm Developers at HRT are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models.

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.

Ideal candidates are excited to apply their research expertise to identify new opportunities in worldwide markets, enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently, and are critical thinkers who can learn and implement new skills in a fast-changing environment.

Qualifications

You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2027 Fluency in Python Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB Brilliant analytical and problem-solving skills Ability to work creatively and independently on long-term technical problems Base salary for US is $300,000. Other locations have similarly locally competitive base salaries. A sign-on and discretionary performance bonus will be provided as part of the total compensation package, in addition to company-paid medical and/or other benefits.

We do not allow multiple applications. Please apply to the ONE role you are most interested in and we will consider you for all open positions when reviewing your application.

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used during any stage of the hiring process, we reserve the right to immediately disqualify your candidacy or rescind any job offers extended.

Locations: London, United Kingdom; New York, NY, United States

Hudson River Trading (HRT) is seeking an AI Research Engineer (Pre-training) to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market and “alternative” data (such as language) to make predictions about future market state.

As a pre-training research engineer on HAIL, you will have a general mandate to improve all aspects of large-scale model training, including but not limited to kernel development, training data loading, parallelism, networking, and fault-tolerance. You will work closely with our researchers to co-design and improve our models, and shape the research agenda.

We have multiple large, modern, and rapidly growing GPU clusters, and we maintain a very high GPU-to-researcher ratio. We are simultaneously pursuing multiple strategies and developing many model types with different purposes, and we are strongly incentivized to squeeze as much as we can out of our systems. Your work will be directly, clearly, and highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions.

Qualifications

Strong engineering skills, especially any of: CUDA/Triton/Pallas/CuTe DSL kernel development, lower-level PyTorch/JAX/XLA development, CUDA Graphs, FPGA/ASIC experience Must have two or more years work experience building deep learning systems, for any domain: robotics, biology, chemistry, physics, audio, video, recommendations, etc. Experience translating methods between areas of application is highly valued LLM experience is valuable, but not necessary Finance experience is not required The estimated base salary range for this position is 250,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used during any stage of the hiring process, we reserve the right to immediately disqualify your candidacy or rescind any job offers extended.

Job Description

At Citadel, our mission is to be the most successful investment team in the world. Quantitative Researchers play a key role in this mission by developing next-generation models and trading approaches for a range of investment strategies. You’ll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world.

Your Objectives

• Conceptualize valuation strategies, develop, and continuously improve upon mathematical models and help translate algorithms into code
• Back test and implement trading models and signals in a live trading environment
• Use unconventional data sources to drive innovation
• Conduct research and statistical analysis to build and refine monetization systems for trading signals

Your Skills & Talents

• PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field
• Strong knowledge of probability and statistics (e.g., machine learning, time-series analysis, pattern recognition, NLP)
• Prior experience working in a data driven research environment
• Experience with translating mathematical models and algorithms into code (Python, R or C++)
• Independent research experience
• Ability to manage multiple tasks and thrive in a fast-paced team environment
• Excellent analytical skills, with strong attention to detail
• Strong written and verbal communication skills

Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel, please share your details and we will contact you if there is a vacancy available.

We collect and use personal data in accordance with our Privacy Policy. We retain data on prospective candidates and may consider suitability for alternative opportunities at Citadel. For more information, see our Privacy Policy.

About Citadel

Citadel is one of the world’s leading alternative investment managers. We manage capital on behalf of many of the world’s preeminent private, public and nonprofit institutions. We seek the highest and best use of investor capital in order to deliver market leading results and contribute to broader economic growth. For over 30 years, Citadel has cultivated a culture of learning and collaboration among some of the most talented and accomplished investment professionals, researchers and engineers in the world. Our colleagues are empowered to test their ideas and develop commercial solutions that accelerate their growth and drive real impact.

The Quantitative Trading & Research (QTR) group is responsible for systematic trading across FX, Rates, Commodities, Credit, Equity and a wide range of markets. Within QTR, AI Market Lab brings together quantitative research, modern artificial intelligence, market microstructure, and high-performance engineering to develop the next generation of electronic trading capabilities. Our work spans signal research, pricing, market making, execution, portfolio construction, risk management, and the production systems that support them. We have positions opened globally across New York, London, Hong Kong, and Singapore and levels are flexible ranging from Associate, to VP, to ED.

As an Associate or Vice President in the QTR Team, you will join as an AI/ML quantitative researcher and bring hands-on experience pre-training large foundation models from scratch. You will lead research on building Transformer-based and time-series foundation models over large-scale market datasets, and develop the methods needed to make them robust, transferable, and measurable across instruments and regimes.

This role is designed for someone who wants to do deep research with real constraints—where questions like scaling laws, data efficiency, and robustness are not academic footnotes, but the core of the agenda.

Job Responsibilities

Pre-train Transformer-based and time-series foundation models from scratch using large-scale market, order-book, transaction, and cross-asset datasets. Develop data representations, tokenization schemes, self-supervised objectives, model architectures, and distributed training recipes for financial time series. Fine-tune and post-train foundation models for alpha generation, pricing, market making, execution, and risk-management tasks. Study scaling laws, transfer across instruments and asset classes, regime robustness, data efficiency, and the trade-offs among model quality, inference cost, and latency. Design evaluation protocols that connect pre-training metrics to economically meaningful outcomes, including out-of-sample prediction, simulated trading, transaction costs, capacity, and live markouts. Build reusable training, checkpointing, evaluation, and model-serving components with ML infrastructure engineers.

Required Qualifications

Advanced degree (Master's, PhD, or equivalent experience) in machine learning, computer science, statistics, mathematics, operations research, engineering, or a related quantitative field. Demonstrated experience pre-training a large model from scratch (Transformer/LLM/multimodal/time-series). Experience limited to API usage or prompt engineering is not sufficient. Experience building large-scale data pipelines and distributed training systems using PyTorch, JAX, or equivalent frameworks. Deep knowledge of large-model training and evaluation: optimization, parallelism, mixed precision, checkpointing, experiment design, ablations, and benchmarking. Evidence of research/technical quality through successful large-model training, high-impact research, open-source systems, or production deployment.

Preferred Qualifications

Experience with fine-tuning/post-training for forecasting, ranking, decision-making, or structured prediction. Prior work on time-series foundation models, limit-order-book modeling, multimodal market data, or cross-asset transfer learning. Experience in quantitative trading, HFT, electronic market making, or systematic investing—especially with models deployed to live trading. Publications at leading ML venues and/or substantial contributions to large-scale model-training systems.

We have roles across 4 locations:

Beijing, China

London, UK

San Francisco, US

Sydney, AU

Vienna, Austria

About Canva

Canva's mission is to empower the world to design, with machine learning playing a central role. Our ML engineers work across product and platform teams, focusing on ranking and search systems, generative models, pipelines, and infrastructure that transform research breakthroughs into features for millions.

About the Role

As a Senior Machine Learning Engineer, you'll own scoped ML problems from start to finish: framing, building, evaluating, shipping, and measuring impact. Depending on your team, you might work on ranking models, generative pipelines, or transitioning research prototypes to production systems. You'll operate with high ownership and minimal guidance, collaborating closely with researchers, product engineers, and platform teams.

What You'll Do

• Build, evaluate, and deploy ML systems in production, handling ranking, relevance, generation, or evaluation infrastructure.
• Own projects from problem framing to measurable impact with minimal guidance.
• Balance production trade-offs like quality, cost, and latency in model integration.
• Investigate and resolve issues in live systems.
• Collaborate with research, product, and platform engineers to create actionable plans.
• Clearly communicate technical trade-offs and share knowledge across teams.

You're Likely a Match If You Have

• Experience deploying ML systems at scale, beyond just model training.
• Ability to define and impact key metrics, not just optimizing model accuracy.
• Proven track record of independently managing projects from idea to completion.
• Strong software engineering skills and proficiency in modern ML tools (e.g., Python, PyTorch).
• High autonomy and adaptability to evolving products and priorities.
• Excellent communication and collaboration skills.

Nice to Have

• Expertise in areas like search and ranking systems, generative model evaluation, distributed training, or MLOps.
• Experience with systems used by millions.
• A history of delivering ML-powered product features end to end.

At Canva, we value fairness, and we strive to provide competitive, market-informed compensation whilst ensuring internal equity within the team in each region. The target salary range for this position is $220,000 - $280,000. When calculating offers, we make salary decisions based on market data and candidates' skills and experience.