NeurIPS 2025 Career Opportunities

Overview

Join our core R&D team building end-to-end automated research systems.

• Zochi publishes the first fully AI-generated A* conference paper (ACL 2025).
  https://www.intology.ai/blog/zochi-acl
• Locus becomes the first AI system to outperform human experts at AI R&D (RE-Bench).
  https://www.intology.ai/blog/previewing-locus

Key Responsibilities

• Design and implement novel architectures for automated research.
• Collaborate with a focused team tackling problems at the forefront of:
• long-horizon agentic capabilities
• post-training for open-ended goals
• environment and benchmark development
• Publish internal key findings and external collaboration success stories.

Qualifications

• PhD or equivalent research experience in Computer Science, Machine Learning, AI, or a related field.
  Exceptional candidates with strong research contributions are encouraged to apply regardless of degree.
• Proven track record of high-impact AI/ML research contributions in academia or industry.
• Expertise in long-horizon or multi-agent systems, and/or model post-training for advanced capabilities.
  Bonus: experience in scientific domains or open-ended discovery systems.
• Passion for accelerating problem-solving and scientific discovery; comfortable in high-autonomy environments.

Our Culture

• Competitive salary & equity packages
• Unlimited PTO with a focus on on-site collaboration and team-building
• Conference attendance & community-facing event involvement
• High agency, ownership, and responsibility
• A small, dedicated group of top investors, researchers, and industry veterans committed to accelerating discovery. Join us.

Successful hires will support our machine learning team by processing and organizing scientific datasets relevant to drug discovery and development. Candidates should have an undergraduate degree in a STEM field, hands-on experience in a Linux environment, and familiarity with Python and SQL. Experience handling large-scale datasets, structuring data from diverse sources, and cataloging metadata to facilitate data discovery and maintain accurate data provenance is highly desirable. This is a two-year position with full benefits. For more information, visit www.DEShawResearch.com.

Please apply using the link below:

https://apply.deshawresearch.com/careers/Register?pipelineId=909&source=NeurIPS_1

The expected annual base salary for this role is USD 160,000 - USD 200,000. Our compensation package includes variable compensation in the form of sign-on and year-end bonuses, as well as generous benefits, including relocation and immigration assistance. The final salary will be determined based on multiple factors, including prior experience and educational background. We follow a hybrid work schedule, with employees working in-office from Tuesday through Thursday and having the option to work remotely on Monday and Friday.

D. E. Shaw Research, LLC is an equal opportunity employer.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Pinterest helps Pinners discover and do what they love. Homefeed is literally the first surface Pinners see when they open the app and so it forms the front-and-center of the Pinterest experience for 400M+ pinners every month. The Homefeed Relevance team’s mission is to recommend inspiring & engaging pins for all our Pinners. We are looking for a Tech Lead Architect who can drive cross-team engineering efforts for shipping ML-driven product experiences to our pinners. You'll have the opportunity to work on various innovative projects of new product experiences, build large-scale low-latency systems and state-of-the-art machine learning models, and deliver great impact to our pinners and business metrics.

What you'll do:

• Improve relevance and the user experience on Homefeed.
• Work on state-of-the-art large-scale applied machine learning projects.
• Improve the efficiency and reliability of large-scale data processing and ML inference pipeline.
• Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost.

What we're looking for:

• Languages: Python, Java.
• Machine Learning: PyTorch, TensorFlow.
• Big data processing: Spark, Hive, MapReduce.
• 7+ years’ experience with recommender systems or user modeling, implementing production ML systems at scale.
• 7+ years’ experience with large-scale distributed backend services.
• Experience working with deep learning and generative AI models.
• Experience closely collaborating with product managers/designers to ship ML-driven user-facing products.
• Bachelor’s in computer science or equivalent experience.

Successful hires will work on developing and applying large language models (LLMs) to problems in molecular science and drug discovery. Responsibilities include:

• Scaling and optimizing large model training and inference workflows on cutting-edge DESRES infrastructure
• Pre-training, including designing data pipelines and distributed/parallel training
• Post-training techniques, such as reinforcement learning, contrastive learning, and instruction tuning
• Multimodal learning and integrating non-text modalities (for example, molecular graphs, 3D structures, and time series)

Ideal candidates will have deep expertise in large-scale machine learning systems, LLM architecture and training, and/or multimodal learning, as well as strong Python programming skills. While the application domains include areas such as drug discovery and biomolecular simulation, specific experience in any of these areas is less critical than intellectual curiosity, versatility, and a track record of achievement and innovation in the field of machine learning. For more information, visit www.DEShawResearch.com.

Please apply using the link below:

https://apply.deshawresearch.com/careers/Register?pipelineId=921&source=NeurIPS_1

The expected annual base salary for this position is USD 300,000 - USD 800,000. Our compensation package also includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits, including relocation and immigration assistance. The applicable annual base salary paid to a successful applicant will be determined based on multiple factors including the nature and extent of prior experience and educational background. We follow a hybrid work schedule, in which employees work from the office on Tuesday through Thursday, and have the option of working from home on Monday and Friday.

D. E. Shaw Research, LLC is an equal opportunity employer.

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. Please visit the Qualcomm NeurIPS home page by clicking the URL to apply.

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

3. Apply to any of the linked positions on our Qualcomm NeurIPS home page. Make sure you REGISTER first before applying. Your resume will stand out.

Noumenal Labs | Remote-friendly | Full-time

Noumenal’s Probabilistic Perception Lab builds systems capable of navigating outdoor environments through probabilistic spatial reasoning and structured uncertainty reduction. We are looking for a Research Engineer with deep experience in probabilistic inference, spatial AI, and structured generative models to drive applied breakthroughs in perception of outdoor environments. You will work closely with researchers, systems engineers, commercial software engineers, and roboticists to build models that integrate 3D geometry, scene composition, uncertainty, and adaptive inference grounded in generative representations. This role is ideal for someone who has operated at the intersection of probabilistic computing, 3D scene understanding, computational neuroscience, and machine learning research, with experience spanning both foundational research and scalable, applied engineering.

What You’ll Do

~ Develop and deploy probabilistic generative models for perception, scene understanding, and spatial reasoning (structured generative models, inverse graphics, Bayesian scene reconstruction) on hardware in a commercial product. ~ Build inference engines for SLAM, 3D reconstruction, object-centric scene modeling, and spatial world models, leveraging MCMC, variational inference, or novel structured inference techniques. ~ Design systems that combine topological, geometric, and probabilistic methods for robust representation of spatial and conceptual structure. ~ Lead and engage in directed engineering efforts to translate novel algorithms into performant systems suited for real-time or near–real-time perception. ~ Collaborate with researchers in probabilistic computing, robotics, and AI to prototype, test, and iterate on models using synthetic and real sensory data.

Required Skills

~ Experience building perception systems in robotics. ~ Ability to translate research concepts into robust, scalable engineering implementations. ~ Strong coding ability in Python and modern ML frameworks (PyTorch, JAX, or TensorFlow). ~ Expertise in probabilistic inference, structured generative models, or Bayesian approaches (MCMC, variational inference, factorized models, hierarchical generative models). ~ Experience in 3D perception and spatial AI, including at least one of: SLAM, object-centric modeling, structured scene representations, or probabilistic inverse graphics frameworks. ~ Commitment to open-source contributions and internal cross-lab collaborations.

Ideal Background

~ Experience with topological data analysis, geometric representations, or mathematical structure in learning systems (e.g., planning in latent spaces). ~ Strong mathematical background (geometry, topology, optimization, or probabilistic modeling). ~ Background working in interdisciplinary research groups (AI, neuroscience, robotics, mathematics). ~ Publications in machine learning, probabilistic modeling, computational neuroscience, or mathematical methods for perception.

What We Offer

~ Close collaboration with researchers in robotics, physics-inspired AI, and spatial intelligence. ~ Access to real-world data for 3D perception and inference experiments. ~ A remote-friendly environment, flexible work culture, competitive salary + equity.

As a Machine Learning Researcher at IMC, your work will directly impact our global trading strategies. You will leverage your superior analytical, mathematical, and computing skills to improve existing models and develop new ones. We will empower you to discover your unique niche and excel, taking on responsibility and ownership from the start. Machine Learning Researchers work closely with Traders and Developers in an environment where problem solving, innovation and teamwork are recognized and rewarded.

USA - Austin, Seattle

Job Overview

At Arm, we’re redefining what’s possible with AI. Whether it’s enabling edge devices to see and hear, empowering cloud platforms to learn at scale, or pioneering energy-efficient compute for autonomous systems - our AI engineers are at the forefront of building a smarter, connected world.

We’re looking for AI Engineers who are excited by the challenges and opportunities AI presents across industries. From optimizing machine learning performance on next-gen processors to contributing to cutting-edge research, if you’re passionate about the future of AI, we want to meet you.

Responsibilities

Depending on your background and experience, you could be involved in:

Designing and optimizing machine learning models for efficient deployment on Arm-based platforms Building high-performance AI software tools, libraries, and compilers Leading system-level architecture for next-gen AI accelerators Partnering with ecosystem collaborators on real-world ML applications Pushing the boundaries of AI/ML research for embedded, edge, or cloud use cases Understanding and working in a deep technology stack to deliver intelligent, efficient compute

Required Skills and Experience

Strong programming skills in Python, C/C++, or similar languages used in AI and high-performance computing Hands-on experience with machine learning frameworks such as TensorFlow, Pytorch, or ONNX Deep technical understanding of AI/ML model development, training, and inference Experience leading the design and architecture of reliable and scalable systems Ability to work across disciplines in a collaborative, technically ambitious, and fast-paced environment Excellent communication skills and problem solving mindset

“Nice to Have” Skills and Experience

Experience in model optimization for performance, efficiency, or deployment Exposure to deploying machine learning models on edge, devices, or mobile platforms Familiarity with Arm architecture and performance analysis tools

New York

Quantitative Researchers (QRs) specialize in a variety of areas, including but not limited to: using sophisticated data analysis skills to build predictive models, driving construction of a complex multi asset portfolio by utilizing large scale portfolio optimization techniques, and developing sophisticated optimization algorithms. Researchers with an exceptional record of achievement in their respective fields and a drive to apply quantitative techniques to investing are encouraged to apply to GQS.

Preference for on-site candidates in San Mateo, CA but remote possible.

BigHat is hiring ML interns for summer 2026! 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!