NeurIPS 2025 Career Opportunities

Shanghai

Key Responsibilities • Building the compute platform and machine learning libraries for large scale machine learning and simulation workloads • Focus on compute platform stability and efficiency on both CPU and GPU clusters, making the platform observable and scalable • Utilize cluster monitoring and profiling tools to identify bottlenecks and optimize both infrastructure and software system • Troubleshoot and resolve issues related to OS, storage, network, and GPUs

Challenges You Will Tackle: design, build and improve our compute platform for PB scale data model training and simulations with a wide range of machine learning models by leveraging our existing research infrastructure.

Requirements: • Solid experience in running production machine learning infrastructure at a large scale • Experience in designing, deploying, profiling and troubleshooting in Linux-based computing environments • Proficiency in containerization, parallel computing and distributed training algorithms • Experience with storage solutions for large scale, cluster-based data intensive workloads

Bonus qualification: • Experience of supporting machine learning researchers or data scientists for production workloads

WHAT YOU CAN EXPECT FROM US: In return for you joining our elite team, you will be offered a competitive salary package as well as access to a plethora of Optiver-perks. To hear more about what it is like to work here and our great culture, apply now and take the first step towards the best career move you will ever make!

DIVERSITY AND INCLUSION Optiver is committed to diversity and inclusion, and it is hardwired through every stage of our hiring process. We encourage applications from candidates from any and all backgrounds, and we welcome requests for reasonable adjustments during the process to ensure that you can best demonstrate your abilities.

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。 Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.

Austin, TX

About the Team

Avride builds autonomous solutions from the ground up, using machine learning as the core of our navigation pipeline. We are evolving our stack to support the next generation of self-driving, leveraging efficient CNNs, Transformers, and MLLMs to solve complex perception and planning challenges. Our goal is to apply the right approach to the right problem, laying the groundwork for unified, data-driven approaches.

About the Role

We are seeking a Machine Learning Engineer to build the infrastructure and ML foundations for advanced autonomous behaviors. You won't just optimize isolated models; you will architect scalable training workflows and high-fidelity components.

This is a strategic position: You will contribute to the critical infrastructure that paves the way for future end-to-end capabilities. You will translate relevant research ideas into production-ready improvements when they prove beneficial, helping prepare our stack for a transition toward unified, learned behaviors.

What You'll Do

• Strengthen Core Modules: Design and refine models for perception, prediction, or planning, enhancing reliability to support future holistic learning approaches.
• Architect Data Foundations: Build scalable pipelines for multimodal datasets, ensuring they support both current needs and future large-scale E2E experiments.
• Advance Training Infra: Develop distributed training workflows capable of handling massive model architectures for next-gen foundation models.
• Bridge Research & Production: Analyze research in relevant fields, identifying specific opportunities to introduce these techniques into our production stack.
• System Integration: Collaborate with engineering teams to ensure individual ML improvements translate into better system-level performance.

What You'll Need

• Strong ML Fundamentals: Mastery of processing and fusing self-driving modalities (multiview camera, sparse LiDAR, vector maps).
• Architectural Expertise: Deep knowledge of modern architectures like Transformers and Attention Mechanisms.
• Applied Experience: 5+ years of combined experience in industry or applied research settings, with a strong grasp of the full lifecycle from data to deployment.
• Technical Proficiency: Python, PyTorch/JAX/TensorFlow, and distributed computing (PySpark, Ray).
• Systems Mindset: Ability to visualize how modular systems evolve into end-to-end learners and the practical challenges of deploying them.
• Research Capability: Ability to distill complex papers into practical engineering roadmaps.

Nice to Have

• Advanced degree in CS, ML, Robotics, or related field.
• Familiarity with World Models, Occupancy Networks, or Joint Perception-Planning.
• Experience with inference optimization (Triton, TensorRT) and embedded hardware.

Miami, Florida

As a ML/Research Engineer at Citadel Securities, you will work closely with researchers to design and build the next generation library for deep learning within the firm. You will combine the best available open-source tools with deep internal expertise in modelling and predicting financial markets. Your work will empower 100+ researchers to iterate faster on their agenda and perform experiments that were not possible before. 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.

New York

As a Data Scientist, you will analyze complex datasets, build predictive models, and generate insights that drive strategic decisions. You’ll partner with engineers, researchers, and business leaders to turn data into actionable outcomes. 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.

Global

Description

Qualcomm is proud to be attending NeurIPS 2025 in our home city San Diego, California! Qualcomm is powering efficient AI from edge to cloud, conducting novel foundational, platform, and applied AI research to enable intelligent computing everywhere.

We're inviting all those who have a passion for AI and are interested in opportunities in generative AI, visual AI, computer vision, and foundational machine learning to please follow the steps below.

1. Go to our Qualcomm - NeurIPS home page.

2 .Register by clicking on the blue link. This allows us to identify your application as someone we met at NeurIPS.

1. Apply to any of the linked positions below. Make sure you REGISTER first before applying. Your resume will stand out.

San Jose, CA, USA

Adobe is looking for a Senior Applied Researcher to use Generative AI and Machine Learning techniques to help Adobe better understand, lead, and optimize the experience of Adobe’s Digital Experience customers. Partnering with Adobe Research and other business units, the candidate will be building products that transform the way companies approach audience creation, journey optimization, and personalization at scale. You will join a diverse, lively group of engineers and scientists long established in the ML space. The work is dynamic, fast-paced, creative, collaborative and data-driven.

NOTE: This role is in the San Jose office. You must be in SJ or willing to relocate for this position.

What you'll do - Partner with Adobe Research to develop cutting edge models! - Design and build applications powered by generative AI, including working on traditional engineering problems such as defining APIs, integrating with UIs, deploying Cloud services, CICD, etc., as well as implementing ML- and LLM-Ops best practices.
- Engage in the product lifecycle, design, deployment, and production operations. - Provide technical leadership in everything from architectural design and technology choices to holistic evaluation of ML models.

What you need to succeed - The ideal candidate will have the following background: - PhD or MS degree in Computer Science, Data Science or related field required.
- 10+ years of applied research experience in software industry/academic research with 5+ years of shown experience developing, evaluating ML models, and deploying models into production. - Deep understanding of statistical modeling, machine learning, or analytics concepts, and a track record of solving problems with these methods; ability to quickly learn new skills and work in a fast-paced team. - Proficient in one or more programming languages such as Python, Scala, Java, SQL. Familiarity with cloud development on Azure/AWS. - Fluent in at least one deep learning framework such as TensorFlow or PyTorch. - Experience with LLMs and emerging area of prompt-engineering. - Recognized as a technical leader in related domain.
- Experience working with both research and product teams.
- Excellent problem-solving and analytic skills - Excellent communication and relationship building skills.

Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview

Susquehanna is expanding the Machine Learning group and seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes.

This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.

What You’ll Do

Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and scalable deployment 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 Develop automation tools to streamline research and system development Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior Partner with engineering teams to implement and test models in production environments

What we're looking for We’re looking for research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning to produce resilient and high-performing models.

PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry settings, with 5+ years of experience building impactful deep learning systems A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR Strong programming skills in Python and/or C++ Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments Hands-on experience applying deep learning on time series data Strong foundation in mathematics, statistics, and algorithm design Excellent problem-solving skills with a creative, research-driven mindset Demonstrated ability to work collaboratively in team-oriented environments A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment

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 Handshake AI builds the data engines that power the next generation of large language models. Our research team works at the intersection of cutting-edge model post-training, rigorous evaluation, and data efficiency. Join us for a focused Summer 2026 internship where your work can ship directly into our production stack and become a publishable research contribution. To start between May and June 2026.

Projects You Could Tackle LLM Post-Training: Novel RLHF / GRPO pipelines, instruction-following refinements, reasoning-trace supervision. LLM Evaluation: New multilingual, long-horizon, or domain-specific benchmarks; automatic vs. human preference studies; robustness diagnostics. Data Efficiency: Active-learning loops, data value estimation, synthetic data generation, and low-resource fine-tuning strategies. Each intern owns a scoped research project, mentored by a senior scientist, with the explicit goal of an archive-ready manuscript or top-tier conference submission.

Desired Capabilities Current PhD student in CS, ML, NLP, or related field. Publication track record at top venues (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.). Hands-on experience training and experimenting with LLMs (e.g., PyTorch, JAX, DeepSpeed, distributed training stacks). Strong empirical rigor and a passion for open-ended AI questions.

Extra Credit Prior work on RLHF, evaluation tooling, or data selection methods. Contributions to open-source LLM frameworks. Public speaking or teaching experience (we often host internal reading groups).

Pinely is a privately owned algorithmic trading firm specializing in high-frequency and mid-frequency trading. We’re based in Amsterdam, Cyprus, and Singapore, and we’re experiencing rapid growth. Pinely is a high-frequency algorithmic trading firm based in Amsterdam. We develop robust and adaptive strategies across diverse markets and actively support the Olympiad movement; many team members are award-winning mathematicians, researchers, and engineers.

Researchers work in a fast-paced HFT environment where ideas quickly reach production. They are supported by a strong infrastructure team enabling large-scale experiments and reliable deployment. Our flat structure encourages autonomy, creativity, and direct impact. We value an informal, idea-driven culture.

We are opening a position for a Junior Deep Learning Researcher in our Amsterdam office.

Responsibilities:

• Conduct research in AI, machine learning, and related quantitative fields
• Develop and experiment with modern deep learning architectures
• Analyze large, unstructured, noisy datasets
• Collaborate with developers and researchers on optimizing trading strategies
• Explore new methods and technologies to improve research outcomes

Requirements:

• Publications in ICML, NeurIPS, ICLR, CVPR, ICCV
• Degree in mathematics, physics, computer science, or another quantitative field (or expected within a year)
• Knowledge of ML, probability theory, and statistics
• Strong Python skills
• Some C++ experience
• Practical experience with modern DL architectures
• Background in working with large noisy datasets

What we offer:

• High base salary with substantial biannual bonuses
• Relocation package to Amsterdam with flexible terms
• Flexible workflow and schedule
• Team of top mathematics and programming competition winners
• Cutting-edge hardware, strong engineering support, and fast idea implementation
• Internal training, comprehensive health insurance, sports reimbursement, and biannual corporate events

Pinely is a privately owned algorithmic trading firm specializing in high-frequency and mid-frequency trading. We’re based in Amsterdam, Cyprus, and Singapore, and we’re experiencing rapid growth. We are seeking a Staff Deep Learning Scientist to drive advanced AI research. This senior individual contributor role focuses on leading technical innovation and shaping research direction across the team. The ideal candidate has deep curiosity, hands-on expertise in neural networks, and prior experience at top AI labs, contributing directly to building and deploying models.

Responsibilities:

• Develop AI models powering every component of end-to-end trading strategies across global markets;
• Tackle the hardest real-world AI problem — predicting financial markets — by understanding deep networks in extremely noisy, diverse, and ever-changing environments;
• Shape research direction and elevate team capabilities through your insights;
• Lead all stages of research from ideation to deployment, ensuring full production integration.

Requirements:

• Senior/Staff/Principal Researcher at a top AI lab or faculty member at a leading institution (Stanford, Berkeley, MIT, CMU, ETH, Mila, UofT, Oxford, UCL, NYU, Princeton, etc.);
• Preferably experienced in competitive AI domains: LLMs, reasoning architectures, generative models (e.g., video), mechanistic interpretability;
• Motivated by deep research and meaningful impact on both the team and the field.

What we offer:

• Significant impact across the company’s entire trading portfolio;
• Competitive compensation with exceptional upside through profit-sharing;
• A research-driven environment where deep technical insight directly influences outcomes;
• Option to work part-time alongside an academic lab;
• A culture that supports initiative, exploration, and high performance;
• Flexible work location: Amsterdam office or fully remote, with optional business travel.