NeurIPS 2025 Career Opportunities

Location Beijing CHINA

Description

1. Mission and Positioning： The Beijing Academy of Artificial Intelligence (BAAI) invites strategic scientists from the global AI community to join us as a Chief Scientist. In this role, you will chart the future course for the Academy's and the discipline's development, guiding our exploration of the AI frontier and establishing yourself as an academic leader shaping the global AI landscape.

2. Qualifications：

3. A distinguished research background at world-leading universities, national-level research institutions, or corporate R&D labs of global renown.
4. A proven record of publishing a series of highly influential research findings in top-tier AI journals and conferences, with the ability to define the frontiers of the discipline.

5. Visionary strategic insight and exceptional academic leadership, with a demonstrated capacity to identify and tackle the field's most fundamental challenges.

6. We Offer：

7. A globally competitive compensation package and comprehensive benefits (customized arrangements are available).
8. Full academic autonomy supported by substantial, long-term research funding and access to world-class computing infrastructure.
9. Full support to assemble and lead an elite research team from around the world.
10. Expedited Beijing residency registration for eligible candidates and access to a premium medical "Green Channel" for senior talent.

11. Customized supplementary health insurance plans for experts and their immediate family members.

12. How to Apply： Please send your detailed CV, representative publications, and a brief research vision statement to: [recruiting@baai.ac.cn] Use the email subject line: "Chief Scientist Application - [Name] - [Primary Research Field]"

D. E. Shaw Research welcomes applications for our summer 2026 internship program from undergraduate and graduate students who are pursuing degrees in scientific and technical disciplines, including machine learning and other areas of computer science, electrical and computer engineering, applied mathematics, physics, chemistry, and chemical or biomolecular engineering. Programming experience in Python or C/C++ is required, and experience with Linux systems, high-performance computing, PyTorch, and/or CUDA would be a plus.

Interns spend 12 to 15 weeks (with flexible start and end dates) working closely with members of our computer science and machine learning team. They are fully immersed in a challenging project involving, for example, applying ML (including large language models) to drug discovery, building and deploying AI-powered systems, developing scientific software, or working on various other engineering and research problems to advance our drug discovery goals. At the end of the summer, interns have the opportunity to give group-wide presentations of their work.

Throughout the summer, interns are invited to attend scientific and technical seminars and workshops, and to join in lively social programming in and around New York City.

For more information, visit www.DEShawResearch.com.

Please apply using the link below:

https://apply.deshawresearch.com/careers/Register?pipelineId=657&source=NeurIPS_1

The expected monthly salary for our internships is USD 11,700 - USD 20,600. The applicable monthly 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 also provide our interns with a generous housing allowance.

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

The role We seek an experienced Senior ML Solutions Architect to support customers leveraging Nebius Token Factory's serverless inference platform for open-source LLMs across multiple modalities. In this role, you will be collaborating with clients to design and implement customized LLM-based solution and architect scalable AI applications using our served models, and working together with our backend team to improve our platform to match the clients' needs.

You’re welcome to work remotely from the United States or Canada.

Your responsibilities will include: - Design and implement LLM-based solutions using Nebius Token Factory’s inference services to drive business value and support customer goals. - Build production-ready applications leveraging our serverless LLM APIs, including multimodal models (text, vision, audio) and domain-specific models. - Provide technical expertise in prompt engineering, RAG architectures, model selection, and inference optimization. - Collaborate with product and engineering teams to surface customer feedback and shape the platform roadmap. - Guide customers in scaling from POC to production with a focus on performance, reliability, and cost efficiency.

We expect you to have: - 5+ years of experience in ML/AI systems, with at least 2 years focused on LLMs and generative AI. - Deep knowledge of the LLM ecosystem, including model architectures and fine-tuning approaches.

Hands-on experience with: - Prompt engineering and LLM pipeline development, including evaluation. - Agentic frameworks such as Langchain, Langsmith, smolagents, or equivalent. - Vector databases and RAG implementation patterns. - Deploying LLM-powered applications using APIs from OpenAI, Anthropic, or open-source models. - Strong Python programming skills. - Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences.

It will be an added bonus if you have: - Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM, Transformers). - Familiarity with inference optimization techniques such as quantization, batching, caching, and routing. - Work with multimodal AI models (e.g., vision-language, speech). - Proficiency with DevOps tools (Docker, Kubernetes). - Contributions to open-source ML/AI projects.

Preferred tooling: - Programming Languages – Python - ML Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, Transformers, OpenAI/Anthropic SDKs - Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent - API and Web Frameworks– FastAPI, Flask - MLOps and DevOps tools– Kubernetes (K8s), Docker, Git - Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

Palo Alto, CA

Position Description: The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI chips tailored to accelerate Tesla’s machine learning capabilities. Their work powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.

Responsibilities: Design, development, and testing of hardware components and systems Work with cross-functional teams to integrate hardware with software and other systems Develop prototypes and proof-of-concepts Influence design decisions through data analysis, provide technical documentation and reports Provide technical documentation and reports

Requirements: Degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field Experience in one of the following areas: AI Accelerators, EDA tools, Physical Design, RTL, DFT, DV, or microarchitecture Strong understanding of hardware design principles and concepts Knowledge and experience with logic design and synthesis tools and techniques Experience with programming languages (e.g., C++, Python, Perl, Linux, MATLAB) Ability to work effectively in a team environment

Salesforce Research is looking for outstanding research interns. Ideal candidates have a strong background in one or more of the following fields:

Conversational AI Multimodal Data Intelligence Multimodal Content Generation Fundamentals of Machine Learning and AI Responsible & Trusted AI Natural Language Processing Areas of Application:

Software Intelligence AI for Operations AI for Availability & Security Environment & Sustainability Candidates that have published in top-tier conferences or journals (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR,) are preferred. As a research intern, you will:

Work with a team of research scientists and engineers on a project that ideally leads to a submission to a top-tier conference

Learn about exciting research and applications outside your expertise

Focus on pure research that incorporates into your PhD focus area and contributes to the AI Community

Attend conferences with our researchers to showcase your accepted papers

Requirements:

PhD candidate in a relevant research area Excellent understanding of deep learning techniques, i.e., CNN, RNN, LSTM, GRU, GAN, attention models, and optimization methods Experience with one or more deep learning libraries and platforms, e.g. PyTorch, TensorFlow, Caffe, or Chainer Strong background in machine learning, natural language processing, computer vision, or reinforcement learning Strong algorithmic problem solving skills Programming experience in Python, Java, C/C++, Lua, or a similar language This internship is a minimum of 12 weeks

Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview

We’re looking for a Machine Learning Systems Engineer to strengthen the performance and scalability of our distributed training infrastructure. In this role, you'll work closely with researchers to streamline the development and execution of large-scale training runs, helping them make the most of our compute resources. You’ll contribute to building tools that make distributed training more efficient and accessible, while continuously refining system performance through careful analysis and optimization. This position is a great fit for someone who enjoys working at the intersection of distributed systems and machine learning, values high-performance code, and has an interest in supporting innovative machine learning efforts.

What You’ll Do

Collaborate with researchers to enable them to develop systems-efficient models and architectures Apply the latest techniques to our internal training runs to achieve impressive hardware efficiency for our training runs Create tooling to help researchers distribute their training jobs more effectively Profile and optimize our training runs

What we're looking for Experience with large-scale ML training pipelines and distributed training frameworks Strong software engineering skills in python Passion for diving deep into systems implementations and understanding fundamentals to improve their performance and maintainability Experience improving resource efficiency across distributed computing environments by leveraging profiling, benchmarking, and implementing system-level optimizations

Why Join Us?

Susquehanna is a global quantitative trading firm that combines deep research, cutting-edge technology, and a collaborative culture. We build most of our systems from the ground up, and innovation is at the core of everything we do. As a Machine Learning Systems Engineer, you’ll play a critical role in shaping the future of AI at Susquehanna — enabling research at scale, accelerating experimentation, and helping unlock new opportunities across the firm.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Los Angeles, CA, 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 is one of the fastest growing online ad platforms, and our success depends on mining rich user interest data that helps us connect users with highly relevant advertisers and products. We’re looking for a leader with experience in machine learning, data mining, and information retrieval to lead a team that develops new data-driven techniques to show the most engaging and relevant promoted content to the users. You’ll be leading a world-class ML team that is growing quickly and laying the foundation for Pinterest’s business success.

What you’ll do:

• Manage and grow the engineering team, providing technical vision and long-term roadmap.
• Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection and yield optimization on the DSP.
• Hire, mentor and grow a team of engineers. Set technical direction, manage project roadmaps, and actively guide team execution. Collaborate across Product, Engineering, Marketing and Sales – translating business goals into ML requirements and ensuring solutions meet cross-functional needs.
• Drive product strategy and advocacy: define and evangelize the ML roadmap for programmatic products, present findings and roadmaps to senior leadership, and work with stakeholders to align analytics projects with company goals (e.g. privacy-first personalization, new DSP features).

What we’re looking for:

• Degree in Computer Science, Machine Learning, Statistics or related field.
• 10+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing.
• Experience in programmatic advertising or information retrieval contexts (RTB, DSP/SSP, search), with familiarity with ad campaign metrics, auction mechanics and yield optimization.
• Excellent cross-functional collaboration and stakeholder communication skills.

San Jose, CA, USA

We are looking for a hands-on, systems-oriented AI Agent Engineer to design, build, and maintain intelligent agents that drive automation and business impact across the enterprise. This role is responsible for the full lifecycle of agent development — from design to versioning, orchestration, and continuous learning.

You’ll contribute directly to scaling our AI strategy by engineering reusable components, optimizing agent workflows, and ensuring real-world performance in production environments.

What you'll Do

• Agent Development: Build and fine-tune specialized AI agents for targeted customer experience use cases such as discovery, support, and lead qualification. Implement prompt engineering strategies, memory handling, resource management and tool-calling integrations

• Multi-Agent Communication: Adopt agent-to-agent communication protocols and handoff mechanisms to enable cooperative task execution and delegation. Build orchestrated workflows across agents using frameworks like LangChain, AutoGen, or Semantic Kernel

• Templates & Reusability: Create reusable agent templates and modular components to accelerate deployment across business units. Build plug-and-play configurations for domain-specific requirements.

• Lifecycle Management & Monitoring: Track and improve conversation quality, task success rate, user satisfaction, and performance metrics. Automate monitoring of agent behavior using observability tools (e.g., Arize, LangSmith, custom dashboards)

• Continuous Improvement: Implement learning workflows, including human-in-the-loop feedback and automatic retraining. Refine prompts and model behavior through structured experimentation and feedback loops.

• Maintenance & Governance: Handle knowledge base updates, drift detection, performance degradation, and integration of new business logic. Ensure agents stay aligned with evolving enterprise data sources and compliance requirements

• Deployment: Manage agent versioning, testing pipelines (unit, regression, UX), and controlled rollout processes. Collaborate with DevOps, QA, and infrastructure teams to ensure scalable deployments

What you need to succeed - 3–5+ years of experience in AI/ML engineering, NLP systems, or backend development - Strong proficiency with LLM frameworks (e.g., OpenAI APIs, LangChain, RAG pipelines) - Experience building conversational agents or workflow bots in production environments - Familiarity with cloud platforms (AWS/GCP/Azure), REST APIs, Python, and containerization (Docker, K8s) - Comfort with prompt design, vector databases, and memory handling strategies

Preferred Qualifications - Experience with multi-agent frameworks or agent orchestration systems - Familiarity with observability tools, data labeling workflows, or synthetic data generation - Background in conversational design or dialogue management systems - Degree in Computer Science, Data Science, Engineering, or a related field

The Deep Learning for Precision Health Lab (www.montillolab.org ), a part of the Biodata Engineering Program of the Biomedical Engineering Department at the University of Texas Southwestern in Dallas, TX seeks a talented and motivated Computational Research Scientist to support large-scale multimodal neuroimaging and biomedical data analysis initiatives and to support advanced AI. The successful candidate will play a key role in curating and analyzing multimodal datasets, preparing resources for foundation model development, and supporting NIH-funded projects at the intersection of machine learning, medical image analysis, neuroscience, and oncology. This is a full-time, long-term staff scientist position focused on technical excellence, reproducible data management, and collaborative research in a dynamic academic environment. The successful candidate’s work will directly inform AI-driven discovery in neurological and oncologic diseases.

With cutting-edge computational infrastructure, access to leading neurology, neuroscience, and cancer experts, and an unparalleled trove of high-dimensional imaging and multi-omic data, our machine learning lab is poised for success in these research endeavors.

Primary Responsibilities

• Configure/develop and run existing foundation or large-scale deep learning models for benchmarking.
• Contribute to manuscript writing and code documentation.
• Curate and manage large neuroimaging & bioimaging datasets that include structural, diffusion, and functional MRI, dynamic PET, EEG, fluorescence microscopy, and multi-omic or clinical data drawn from NIH-supported consortia.
• Develop and maintain automated pipelines for data quality control and reproducibility.
• Clean and prepare datasets for downstream ML and deep-learning workflows.

Qualifications

• M.S. or Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, Physics, Statistics, or a closely related computational field.
• Candidates must have extensive neuroimaging and biomedical image analysis experience.
• Candidates must have existing mastery of one or more mainstream DL frameworks (e.g., PyTorch, TensorFlow) and be able to explain intricacies of the DL models they have constructed.
• Experience running and managing batch jobs on SLURM or similar HPC systems.
• Preferred: familiarity with neuroimaging data formats (DICOM, NIfTI, HDF5, MP4, EEG) and web-scraping or data-discovery scripting.

Compensation and Appointment

• Term and Location: Full-time, On-site in Dallas, TX (5 days/week)
• Salary: Highly competitive and commensurate with experience.
• Work Authorization: Must be legally authorized to work in the U.S.
• Mentorship: Direct supervision by Dr. Albert Montillo with opportunities for co-authorship and professional growth in mentoring junior team members and leading publications.

For consideration:

Reach out for an in-person meeting in San Diego at NeurIPS 2025 (or virtually afterwards) via email to Albert.Montillo@UTSouthwestern.edu with the subject “ComputationalResearchScientist-Applicant-NeurIPS” and include: (1) CV, (2) contact information for 3 references, (3) up to three representative publications, and (4) your start window. Positions are open until filled; review begins immediately.

London

Description - Bloomberg’s Engineering AI department has 350+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Artificial Intelligence (AI) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.

At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 1 billion proprietary and third-party data points published daily -- across all asset classes -- searchable, discoverable, and actionable.

Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.

We are looking for Senior GenAI Platform Engineers with strong expertise and passion for building platforms, especially for GenAI systems.

As a Senior GenAI Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed GenAI development life cycle to enable the building and maintenance of our ML systems. Our teams make extensive use of open source technologies such as Kubernetes, KServe, MCP, Envoy AI Gateway, Buildpacks and other cloud-native and GenAI technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.

Join the AI Group as a Senior GenAI Platform Engineer and you will have the opportunity to: -Architect, build, and diagnose multi-tenant GenAI platform systems -Work closely with GenAI application teams to design seamless workflows for continuous model training, inference, and monitoring -Interface with both GenAI experts to understand workflows, pinpoint and resolve inefficiencies, and inform the next set of features for the platforms -Collaborate with open-source communities and GenAI application teams to build a cohesive development experience -Troubleshoot and debug user issues -Provide operational and user-facing documentation

We are looking for a Senior GenAI Platform Engineer with: -Proven years of experience working with an object-oriented programming language (Python, Go, etc.) -Experience with GenAI technologies like MCP, A2A, Langgraph, LlamaIndex, Pydantic AI, OpenAI APIs and SDKs -A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience -An understanding of Computer Science fundamentals such as data structures and algorithms -An honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management