AISTATS 2026 Career Opportunities

The D. E. Shaw group seeks a highly motivated and entrepreneurial technical product engineer to join its newly formed private equity venture, Cove, and help build the AI-powered platform at its core. This role sits at the intersection of product strategy and technical execution, offering the opportunity to define, shape, and deliver technology solutions that will become the operational backbone of the group. As an early team member, this product engineer will play a key role in addressing the open challenge of applying AI to private equity investments and operations, with the backing of one of the most technologically sophisticated investment firms in the world.

What you'll do day-to-day

You'll be involved in all aspects of building and scaling technology products for the fund's investment activities, including: - Work closely with the investment and operations teams to surface high-impact opportunities, pressure-test ideas, and translate workflow challenges into clear product direction. - Own product design end-to-end—from how data is structured and connected to the business logic that determines how a tool actually behaves—bringing both conceptual clarity and technical precision to each iteration. - Design and build AI-native products that use LLMs to change how investment teams work, with a solid intuition for how model behavior shapes user experience and where AI can add genuine leverage. - Drive products from prototype to production, contributing code directly—especially in early stages—when tight product and business judgment matters most.

Who we're looking for

• A bachelor’s degree or higher, an impressive record of academic and professional achievement, and at least five years of relevant experience.
• At least two years of experience developing technology products in direct collaboration with engineering teams, including at least one year focused on workflow products that streamline business operations and processes.
• Experience successfully taking a product from conception to completion, ideally in a startup environment; prior experience developing products for vertical-specific or industry-focused applications is a plus.
• A solid technical foundation in full-stack product development—spanning APIs, databases, and user interfaces—with the ability to read and execute code, and proficiency in overseeing technical aspects from architecture decisions to implementation details.
• At least one year of experience developing and integrating LLM-powered systems into production applications, with knowledge of agentic frameworks and their practical implementation; demonstrated ability to translate AI capabilities (including autonomous agents, tool use, and multi-step reasoning) into practical product features that solve real-world problems.
• Well-developed communication skills, a collaborative and entrepreneurial mindset, and the ability to successfully manage multiple projects at once.
• The expected annual base salary for this position is $185,000 to $250,000. Our compensation and benefits package includes variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

Quants at the D. E. Shaw group apply mathematical techniques and write software to develop, analyze, and implement statistical models for our computerized financial trading strategies. They utilize their creativity and innovation to create novel approaches to trade profitably in markets around the globe with a firm that offers a collegial, collaborative, and engaging working environment.

What you'll do day-to-day

Specific responsibilities range from leveraging financial data in an effort to increase profitability, decrease risk, and reduce transaction costs to conceiving new trading ideas, formulating them into systematic strategies, and critically evaluating their performance.

Who we're looking for

• Successful candidates will have impressive records of academic achievement and be the top students in their respective math, statistics, physics, engineering, computer science, and other technical and quantitative programs.
• The expected annual base salary for this position is $275,000 for applicants who have completed undergraduate or master’s degrees and $300,000 for applicants who have completed PhDs (or have comparable professional experience). Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, a relocation bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

The D. E. Shaw group seeks a machine learning researcher to creatively apply their knowledge of ML and software engineering to design and build computational architectures for high-performance, large-scale knowledge discovery in financial data. In this dynamic role, the engineer will leverage cutting-edge ML research to turn new ideas into proof-of-concept implementations, solve tough low-level engineering problems, and set up infrastructure for broader, longer-term impact. This position will play a key role in improving the efficiency, scalability, and reliability of the firm’s ML efforts, and will directly impact the firm’s systematic research through ML engineering contributions, all within a collaborative and engaging environment.

What you'll do day-to-day

• Rapidly prototype, implement, and evaluate state-of-the-art machine learning techniques.
• Drive the computational agenda for ongoing and future ML projects.
• Tackle complex engineering problems across software and hardware layers, setting technical direction and anticipating architectural needs.
• Deploy ML models into real-world systems where they have direct, measurable impact on decision-making and trading.
• Create compelling proof-of-concept systems, demonstrate them internally, and collaborate with others for development.
• Partner with researchers to design and implement efficient training workflows, enabling rapid experimentation with deep learning models.

Who we're looking for

• Bachelor’s degree or higher is required.
• Proven track record of collaborating with researchers to translate ML ideas into high-performance solutions.
• Experience driving computational and architectural innovation by rapidly prototyping and demonstrating novel ML ideas within a high-performance environment.
• Interest in staying current with ML research and swift application of new techniques.
• Expertise in performance optimization, low-level engineering, GPU programming and libraries (e.g., Pytorch, JAX, CUDA, XLA, Triton, or PTX).
• Demonstrated ability to quickly solve complex computational problems, create inspiring technical demos, and transition work to broader teams.
• Proactive approach in driving agendas and anticipating engineering bottlenecks in large systems.
• Proficiency in modern ML frameworks, facility with deep learning tooling, and a solid understanding of hardware and architectural challenges.
• The expected annual base salary for this position is $275,000 to $350,000. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

The D. E. Shaw group seeks exceptional software engineers with expertise in applied AI, AI agents, and agentic systems to join the firm. This role offers the chance to work directly with a variety of groups at the firm on innovative, greenfield projects that transform how teams operate—leveraging quantitative and programming skills to design, build, and deploy AI solutions that drive efficiency, enhance analytical capabilities, and accelerate decision-making across the firm.

What you'll do day-to-day

You’ll join a dynamic team, with the potential to: - Collaborate directly with internal groups and end users across various functions to build bespoke AI agents and applications tailored to nuanced, real-world business needs. - Lead and contribute to greenfield AI projects, taking ownership from concept through production and helping shape internal AI strategy and adoption. - Experiment with emerging AI tools and model capabilities, rapidly prototyping and integrating them across platforms to enhance usability, scalability, and effectiveness. - Scale the adoption of AI tools firmwide by developing best practices, frameworks, and reusable components that drive innovation and productivity. - Build foundational AI components, such as agent frameworks, reusable “skills,” and large-scale retrieval systems, to support AI tools and applications. - Design, develop, and maintain shared AI infrastructure and agentic applications, ensuring firmwide data integration and enhancing software development efficiency.

Who we're looking for

• A bachelor’s degree in any field is required, along with an extensive background in software development, and hands-on experience building and scaling AI solutions at the product, system, or company level.
• Solid understanding of AI technologies and an interest in developing advanced AI applications and frameworks.
• Demonstrated ability to thrive in technical or entrepreneurial environments, along with the capability to solve complex challenges and lead projects from inception to deployment.
• A record of strong academic or professional achievement, with analytical depth and creativity in AI-related projects.
• We welcome outstanding candidates at all experience levels who are excited to work in a collegial, collaborative, and fast-paced environment.
• The expected annual base salary for this position is $225,000 to $275,000. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

NYC, Cambridge MA, and London UK

**Basis Research Institute** is a 501(c)(3) nonprofit AI research institute with a vision to build a universal reasoning engine to advance science and solve problems of societal importance. We're expanding our team and have multiple positions open, including full-time research roles and postdoctoral fellowship positions, in NYC and Cambridge, MA. We also anticipate positions open in London, UK in the future.

Research Scientists and Engineers: We’re looking for Research Scientists and Engineers with experience in probabilistic machine learning, causal inference, model discovery, programming languages, compiler design, robotics, and related areas. If you’re excited to contribute to Basis’ technical mission, we encourage you to apply.

Postdocs: Our Postdoctoral Fellowship offers the opportunity to work both with Basis scientists, contributing to Basis technology, and with academic PIs by mutual agreement. More details here.

Full listing of open roles here, including in Operations & Programs and Applied AI & Engineering.

Stop by our sponsor booth to learn more.

Feel free to reach out to contact@basis.ai with questions.

Location: London

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.

From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.

Join a research team where curiosity meets scale. You’ll investigate foundational questions, uncover market insights and push the boundaries of what's possible - all with the support of near-limitless compute and world-class peers.

Take the next step in your career.

The role 10-week summer programme (22nd June to 28th August 2026)

09:00-17:30 working hours

Based in Central London

Over the course of 10 weeks, G-Research Summer Research Programme interns gain a unique insight into life as a Machine Learning (ML) practitioner at a leading quantitative finance research firm.

Our full-time ML researchers use a wide range of tools and techniques in an applied setting, putting their expertise to use in direct, production-ready applications with immediate results. They have access to vast computing resources and are limited only by their imagination.

As an ML intern, you will have the opportunity to experience some of this as part of a 10-week programme working on a meaningful and challenging research project that demands the application of innovative yet pragmatic mathematical and computational analysis.

You will be paired with a mentor who will supervise your work and provide ongoing feedback to help you improve and develop, as well as access to senior staff who are leaders in their fields. Your internship will culminate in a final presentation of your research ideas to senior management.

Taking part in G-Research's Summer Internship Programme will give you an in-depth insight into our academic approach to the world of quantitative finance and allow you to explore the thriving city of London, while you get to know your fellow interns and colleagues through a full itinerary of fun social events.

Top performers on the programme will be considered for full-time opportunities on completion of their studies.

Who are we looking for? The ideal candidate will, at a minimum, have experience in the following areas:

A post-graduate degree in Machine Learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle. PhD level study is preferred

Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference

Excellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don't always work with our data, so you will need to understand how to develop your own models

Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter

Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here.

Why should you apply? Highly competitive compensation plus accommodation G-Research community with weekly intern activities Lunch provided (via Just Eat for Business) and dedicated barista bar 30 days’ annual leave pro-rated

Informal dress code and excellent work/life balance Central London office close to 5 stations and 6 tube lines

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.

From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.

Join a research team where curiosity meets scale. You’ll investigate foundational questions, uncover market insights and push the boundaries of what's possible - all with the support of near-limitless compute and world-class peers.

Take the next step in your career.

The role Our researchers have a challenge: disproving the efficient market hypothesis every day. This requires them to harness massive compute power and to use state-of-the-art ML techniques – published in recent conferences or developed entirely in-house – as textbook methods won’t beat the competition.

ML is integral to develop successful investment management strategies; it is one of the core drivers of our overall performance and success. It has long been a key tool at G-Research and we count a range of ICML and NeurIPS published researchers among our people.

Our ML practitioners have huge amounts of (clean) data and near infinite compute at their fingertips, with which they’re incentivised to explore the cutting-edge and find the 1% of difference. And unlike pure problems, our researchers get near instantaneous feedback in the form of absolute numbers where success is highly measurable and has a direct impact on the business.

As a team, we read the latest publications in the field and discuss them within the our vibrant, collaborative research community, and attend the leading conferences worldwide, such as NeurIPS and ICML.

In this research role you will be able to develop and test your ideas with real-world data in an academic environment.

Who are we looking for? The ideal candidate will have:

Either a post-graduate degree in machine learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference Excellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don’t always work on our data so you will need to understand how to develop your own models Strong programming skills and experience working with Python, Scikit-Learn, SciPy, NumPy, Pandas and Jupyter Notebooks is desirable. Experience with object-oriented programming is beneficial Publications at top conferences, such as NeurIPS, ICML or ICLR, is highly desirable

Why should you apply? Highly competitive compensation plus annual discretionary bonus Lunch provided (via Just Eat for Business) and dedicated barista bar 35 days’ annual leave 9% company pension contributions Informal dress code and excellent work/life balance Comprehensive healthcare and life assurance Cycle-to-work scheme Monthly company events