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NeurIPS 2025 Career Opportunities

Here we highlight career opportunities submitted by our Exhibitors, and other top industry, academic, and non-profit leaders. We would like to thank each of our exhibitors for supporting NeurIPS 2025.

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Global - United States, Europe, Asia


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.

San Francisco


About this role

We’re looking for a Data Engineer to help design, build, and scale the data infrastructure that powers our analytics, reporting, and product insights. As part of a small but high-impact Data team, you’ll define the architectural foundation and tooling for our end-to-end data ecosystem.

You’ll work closely with engineering, product, and business stakeholders to build robust pipelines, scalable data models, and reliable workflows that enable data-driven decisions across the company. If you are passionate about data infrastructure, and solving complex data problems, we want to hear from you!

Tech stack

Core tools: Snowflake, BigQuery, dbt, Fivetran, Hightouch, Segment Periphery tools: AWS DMS, Google Datastream, Terraform, GithHub Actions

What you’ll do

Data infrastructure: * Design efficient and reusable data models optimized for analytical and operational workloads. * Design and maintain scalable, fault-tolerant data pipelines and ingestion frameworks across multiple data sources. * Architect and optimize our data warehouse (Snowflake/BigQuery) to ensure performance, cost efficiency, and security. * Define and implement data governance frameworks — schema management, lineage tracking, and access control.

Data orchestration: * Build and manage robust ETL workflows using dbt and orchestration tools (e.g., Airflow, Prefect). * Implement monitoring, alerting, and logging to ensure pipeline observability and reliability. * Lead automation initiatives to reduce manual operations and improve data workflow efficiency.

Data quality: * Develop comprehensive data validation, testing, and anomaly detection systems. * Establish SLAs for key data assets and proactively address pipeline or data quality issues. * Implement versioning, modularity, and performance best practices within dbt and SQL.

Collaboration & leadership: * Partner with product and engineering teams to deliver data solutions that align with downstream use cases. * Establish data engineering best practices and serve as a subject matter expert on our data pipelines, models and systems.

What we’re looking for

  • 5+ years of hands-on experience in a data engineering role, ideally in a SaaS environment.
  • Expert-level proficiency in SQL, dbt, and Python.
  • Strong experience with data pipeline orchestration (Airflow, Prefect, Dagster, etc.) and CI/CD for data workflows.
  • Deep understanding of cloud-based data architectures (AWS, GCP) — including networking, IAM, and security best practices.
  • Experience with event-driven systems (Kafka, Pub/Sub, Kinesis) and real-time data streaming is a plus.
  • Strong grasp of data modeling principles, warehouse optimization, and cost management.
  • Passionate about data reliability, testing, and monitoring — you treat pipelines like production software.
  • Thrive in ambiguous, fast-moving environments and enjoy building systems from the ground up.

Bala Cynwyd (Philadelphia Area), Pennsylvania United States & New York, New York United States


Overview

Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.

As a Machine Learning Intern at Susquehanna, you’ll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You’ll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.

What You Can Expect

 • Conduct research and develop ML models to identify patterns in noisy, non-stationary data

 • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation

 • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches

 • Design and run experiments using the latest ML tools and frameworks

 • One-on-one mentorship from experienced researchers and technologists

 • Participate in a comprehensive education program with deep dives into Susquehanna’s ML, quant, and trading practices

 • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior

 • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for

 • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field

 • Proven experience applying machine learning techniques in a professional or academic setting

 • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR

 • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow

 • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?

 • Work with a world-class team of researchers and technologists

 • Access to unparalleled financial data and computing resources

 • Opportunity to make a direct impact on trading performance

 • Collaborative, intellectually stimulating environment with global reach

Location Hybrid (2-3 days a week) on-site in San Mateo, CA.


BigHat is opening an ML Fellowship. We've got an awesome high-throughput wetlab that pumps proprietary data into custom data and ML Ops infra to power our weekly design-build-train loop. Come solve hard-enough-to-be-fun problems in protein engineering in service of helping patients!

Location - SF Bay Area | Boston

Description - We're always looking for exceptional researchers and engineers to join our team. If you're passionate about advancing AI research and engineering in meaningful ways but don't see a specific role that matches your background, we encourage you to apply through this general application.

We're interested in candidates across the research and engineering spectrum, including:

  • Research Scientists: Those focused on developing novel AI methodologies, conducting fundamental research, and publishing cutting-edge work
  • Research Engineers: Those who excel at rapidly implementing and iterating on experimental AI systems and prototypes

More Information

Company background and additional context on the types of researchers and engineers we’re looking for can be found here: https://www.notion.so/afterthought/General-Application-Research-Engineers-and-Researcher-2bf9d66a8cc3801bbf01e6b4b5ab4924

New York


Quantitative Analyst Ph.D. Intern (New York) – Summer 2026

The D. E. Shaw group seeks talented Ph.D. candidates with impressive records of academic and/or professional achievement to join the firm as quantitative analyst interns. Ph.D. interns explore how the analytical skills gained from their graduate programs may relate to the work done at the firm while interacting with fellow interns and employees of similar academic backgrounds in a collegial working environment. This 12-week program will take place in New York and is expected to run from June to August 2026. 

What you'll do day-to-day

You’ll spend the summer working on a research project that typically involves exploring a variety of statistical modeling techniques and writing software to analyze financial data. You’ll have a dedicated mentor in one of our quantitative research groups and are encouraged to attend our academic speaker series and track academic progress in various areas that may be of interest.

Who we're looking for

  • Individuals with impressive records of academic achievement, including advanced coursework in fields such as math, statistics, physics, engineering, computer science, or other technical and quantitative programs. 
  • Applicants should have notable research productivity in their respective areas of study as well as a track record of creativity in their field(s). 
  • Interest or experience working in a data-driven research environment, including manipulation of data using high-level programming languages such as Python, is preferred. 
  • An exceptional aptitude for abstract reasoning, problem solving, and quantitative thinking, in addition to prior probability or statistics knowledge, is a plus. 
  • No previous finance experience is necessary, though candidates should have an interest in learning about quantitative finance.
  • Students who apply to this internship are usually approaching their final year of full-time study.
  • The position offers a monthly base salary of 25,000USD, overtime pay, a sign-on bonus of 25,000USD, travel coverage to and from the internship, and choice of furnished summer housing or a 10,000USD housing allowance. It also includes a 3,300USD stipend for self-study materials and a 4,000USD stipend for personal technology equipment. If you have any questions about the compensation, please ask one of our recruiters.

We are now looking for a Senior Research Scientist focused on Multimodal Foundation Models and Robotics! NVIDIA is searching for an outstanding research scientist to build humanoid robot foundation models and systems in the Generalist Embodied Agent Research (GEAR) group. Everything that moves will eventually be autonomous. Our mission is to build general-purpose embodied agents that learn to explore and master complex skills across the virtual and the physical world.

You will work with an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, game AI, and physical simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and more. One of our team’s most recent milestones includes Project GR00T, a foundation model for humanoid robots. Your contributions will have a significant impact on our moonshot research projects and product roadmaps.

What you will be doing: Design and implement novel AI algorithms and models for general-purpose humanoid robots and embodied agents;

Develop large-scale AI training and inference methods for foundation models;

Optimize and deploy AI models in physical simulation and on robot hardware;

Collaborate with research and engineering teams across all of NVIDIA to transfer research to products and services.

What we need to see: A Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience.

5 years of relevant work/research experience across one or both of these fields: Multimodal Foundation Models

Hands-on training experience and publications in at least one of the following topics: LLMs; Large vision-language models; Video generative models and diffusion algorithms; or Action-based transformers.

Outstanding engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow, etc.). Python is required; C++ and CUDA proficiencies are a big plus;

Excellent skills in working with large-scale machine learning/AI systems and compute infrastructure.

Robotics: Hands-on training experience and publications in robot learning, such as reinforcement learning, imitation learning, classical control methods, etc.

Strong programming skills in Python, C++, ROS, and machine learning frameworks like PyTorch.

Deep understanding of robot kinematics, dynamics, and sensors;

Ability to safely operate robot hardware, lab equipment, and tools;

Knowledge of control methods, including PID, model predictive control, and whole-body control;

Familiarity with physics simulation frameworks such as MuJoCo and Isaac Sim;

Robot hardware design and hands-on building experience.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and embodied agents!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 299,000 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Location Chicago; New York

Description:

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.

Other duties as assigned or needed.

Skills You’ll Need:

  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
  • Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
  • Solid development skills in Python and/or C++
  • Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, and/or JAX
  • Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
  • Ability to thrive in a collaborative, team-oriented environment
  • Ability to reason through quantitative problems and communicate effectively with trading researchers
  • Reliable and predictable availability required

Bonus Points:

  • Experience with HPC and distributed large model training
  • Experience with GPU performance optimization (CUDA or ROCm)
  • Experience with end-to-end model development
  • Strong opinions on best practices in ML research, tooling, and/or infrastructure

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role is $300,000 per year.

About Handshake AI Handshake is building the career network for the AI economy. Our three-sided marketplace connects 18 million students and alumni, 1,500+ academic institutions across the U.S. and Europe, and 1 million employers to power how the next generation explores careers, builds skills, and gets hired. Handshake AI is a human data labeling business that leverages the scale of the largest early career network. We work directly with the world’s leading AI research labs to build a new generation of human data products. From PhDs in physics to undergrads fluent in LLMs, Handshake AI is the trusted partner for domain-specific data and evaluation at scale. This is a unique opportunity to join a fast-growing team shaping the future of AI through better data, better tools, and better systems—for experts, by experts.

Now’s a great time to join Handshake. Here’s why: Leading the AI Career Revolution: Be part of the team redefining work in the AI economy for millions worldwide. Proven Market Demand: Deep employer partnerships across Fortune 500s and the world’s leading AI research labs. World-Class Team: Leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, just to name a few. Capitalized & Scaling: $3.5B valuation from top investors including Kleiner Perkins, True Ventures, Notable Capital, and more.

About the Role As a Staff Research Scientist, you will drive frontier research on how we define intelligence of frontier models, i.e. develop benchmarks and measurements that help the research community to understand how large language models (LLMs) understand, reason, and interact with human knowledge. You will: Lead teams of researchers to produce original research in LLM evaluation methodologies, interpretability, and human-AI knowledge alignment. Develop novel frameworks and assessment techniques that reveal deep insights into model capabilities, limitations, and emergent behaviors. Collaborate with engineers to translate research breakthroughs into scalable benchmarks, evaluation systems, and standards. Pioneer new approaches to measuring reasoning, alignment, and trustworthiness in frontier AI systems. Author high-quality code to enable large-scale experimentation, reproducible evaluation, and knowledge assessment workflows. Publish in top-tier conferences and journals, establishing new directions in the science of AI evaluation. Work cross-functionally with leadership, engineers, and external partners to set industry standards for responsible AI evaluation and alignment.

Desired Capabilities PhD or equivalent research experience in machine learning, computer science, cognitive science, or related fields with focus on AI evaluation, interpretability, or model understanding. 6+ years of academic or industry experience post-doc in a research-first environment Strong background in LLM research, evaluation methodologies, and/or foundational AI assessment techniques. Proven ability to independently design, lead, and execute evaluation research programs with novel data types end-to-end. Deep proficiency in Python and PyTorch for large-scale model analysis, benchmarking, and evaluation. Experience building or leading novel benchmark development, systematic model assessment, or interpretability studies. Strong publication record in post-training, evaluation, or interpretability that demonstrates field-defining contributions. Ability to clearly communicate complex insights and influence both technical and non-technical stakeholders.

Extra Credit Experience with RLHF, agent modeling, or AI alignment research. Familiarity with data-centric AI approaches, synthetic data generation, or human-in-the-loop systems. Understanding of challenges in scaling foundation models (training stability, safety, inference efficiency). Contributions to open-source libraries or research tooling. Interest in the societal impact, deployment ethics, and governance of frontier AI systems.

Open positions in Mathematical, Statistical and Computational aspects of Artificial Intelligence and Machine Learning.

The Faculty of Mathematics and the Institute for Mathematical and Computational Engineering (IMC) from the Pontificia Universidad Católica de Chile (UC) are offering up to two full-time professor positions at the assistant or associate level. The successful candidate will have a joint appointment between the Faculty of Mathematics and the IMC. We welcome applications from highly qualified candidates with a track record of excellent research and a solid commitment to excellence in teaching and supervision. This position is intended for those researchers interested in advancing the mathematical, statistical and computational aspects of modern artificial intelligence, machine learning and its applications. Candidates conducting research in areas including pure and computational mathematics, mathematical modeling, statistics, optimization, and theoretical computer science, that exhibit a convincing path towards AI research are also encouraged to apply.

The successful candidate will contribute to teaching courses at the Institute for Mathematical and Computational Engineering and the Faculty of Mathematics. The typical teaching load is three semester-long courses a year, at the graduate or undergraduate level, split between the two academic units. Command of Spanish is not required for applying; however, the selected candidate is expected to start teaching in Spanish in at most two years. Applicants who do not speak Spanish will receive support from the University to learn the language adequately. To support the initial academic career stages, the incorporation of Assistant Professors can benefit from an initial reduction of the teaching load and a starting fund. The applicant position and salary will be adjusted, according to the policies and regulations at UC, on the applicant starting date. These will be determined according to the previous experience of the candidate. UC is committed to the values of diversity regarding origin, gender, and ethnicity to build a more diverse and inclusive community. For the current call, women are especially encouraged to apply.

APPLICATIONS

Applications are received through MATHJOBS platform at the link https://www.mathjobs.org/jobs/list/27675 or can be sent by email at vacancysearch.imc@uc.cl. The documentation submitted must include at least:

  • Cover letter.
  • Curriculum vitae.
  • Publication list.
  • Research statement.
  • Teaching statement.
  • Three (3) letters of recommendation, with ideally at least one of them referring to the teaching experience.

The deadline for the applications is December 16th, 2025. Queries can be made by email to Prof. Cristóbal Rojas at vacancysearch.imc@uc.cl.

VISA

If selected for a position, a foreigner without permanent residency in Chile or applying from abroad will need to request a visa in the consulate of their country of origin to be incorporated as academic staff at UC Chile.

Further information about IMC and the Faculty of Mathematics can be found at https://imc.uc.cl and www.mat.uc.cl.