NeurIPS 2025 Career Opportunities

We are Bagel Labs - a distributed machine learning research lab working toward open-source superintelligence.

Role Overview

You will design and optimize distributed diffusion model training and serving systems.
Your mission is to build scalable, fault-tolerant infrastructure that serves open-source diffusion models across multiple nodes and regions with efficient adaptation support.

Key Responsibilities

• Design and implement distributed diffusion inference systems for image, video, and multimodal generation.
• Architect high-availability clusters with failover, load balancing, and dynamic batching for variable resolutions.
• Build monitoring and observability systems for denoising steps, memory usage, generation latency, and CLIP score tracking.
• Integrate with open-source frameworks such as Diffusers, ComfyUI, and Invoke AI.
• Implement and optimize rectified flow, consistency distillation, and progressive distillation.
• Design distributed systems for ControlNet, IP-Adapter, and multimodal conditioning at scale.
• Build infrastructure for LoRA/LyCORIS adaptation with hot-swapping and memory-efficient merging.
• Optimize VAE decoding pipelines and implement tiled/windowed generation for ultra-high-resolution outputs.
• Document architectural decisions, review code, and publish technical deep-dives on blog.bagel.com.

Who You Might Be

You understand distributed systems and diffusion architectures deeply.
You’re excited about the evolution from DDPM to flow matching to consistency models, and you enjoy building infrastructure that handles complex, variable compute workloads.

Required Skills

1. 5+ years in distributed systems or production ML serving.
2. Hands-on experience with Diffusers, ComfyUI, or similar frameworks in production.
3. Deep understanding of diffusion architectures (U-Net, DiT, rectified flows, consistency models).
4. Experience with distributed GPU orchestration for high-memory workloads.
5. Proven record of optimizing generation latency (CFG, DDIM/DPM solvers, distillation).
6. Familiarity with attention optimization (Flash Attention, xFormers, memory-efficient attention).
7. Strong grasp of adaptation techniques (LoRA, LyCORIS, textual inversion, DreamBooth).
8. Skilled in variable-resolution generation and dynamic batching strategies.

Bonus Skills

• Contributions to open-source diffusion frameworks or research.
• Experience with video diffusion models and temporal consistency optimization.
• Knowledge of quantization techniques (INT8, mixed precision) for diffusion models.
• Experience with SDXL, Stable Cascade, Würstchen, or latent consistency models.
• Distributed training using EDM, v-prediction, or zero-terminal SNR.
• Familiarity with CLIP guidance, perceptual loss, and aesthetic scoring.
• Experience with real-time diffusion inference (consistency or adversarial distillation).
• Published work or talks on diffusion inference optimization.

What We Offer

• Top-of-market compensation
• A deeply technical culture where bold ideas are built, not just discussed
• Remote flexibility within North American time zones
• Ownership of work shaping decentralized AI
• Paid travel to leading ML conferences worldwide

Apply now - help us build the infrastructure for open-source superintelligence.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; New York, NY, 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.

Within the Monetization ML Engineering organization, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. As a Distinguished Machine Learning Engineer, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack for Monetization. You will work on tackling new challenges in machine learning and deep learning to advance the statistical models that power ads performance and ads delivery that bring together Pinners and partners in this unique marketplace.

What you'll do:

• Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML.
• Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery.
• Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost.
• Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements.
• Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals.
• Champion engineering excellence and a data driven culture, mentor senior tech talent and represent Pinterest externally in the tech and AI communities.

What we’re looking for:

• Degree in computer science, machine learning, statistics, or a related field.
• 15+ years of working experience in engineering teams that build large-scale, ML‑driven, user‑facing products.
• Experience leading cross‑team engineering efforts that improve user experience in products.
• Understanding of an object‑oriented programming language such as Go, Java, C++, or Python.
• Experience with large‑scale data processing (e.g., Hive, Scalding, Spark, Hadoop, MapReduce).
• Strong software engineering and mathematical skills, with knowledge of statistical methods.
• Experience working across frontend, backend, and ML systems for large‑scale user‑facing products, with a good understanding of how they all work together.
• Hands‑on experience with large‑scale online e‑commerce systems.
• Background in computational advertising is preferred.
• Excellent cross‑functional collaboration and stakeholder communication skills, with strong execution in project management.

New York

Software Developer: Generative AI Product Development

The D. E. Shaw group seeks exceptional software developers with expertise in generative AI (GAI) to join a small, fast-moving team building greenfield GAI products that directly transform how our teams operate. In this hands-on, entrepreneurial role you’ll partner with users across the firm to design, build, and deploy bespoke GAI solutions that drive efficiency, enhance analytical capabilities, and accelerate decision-making. This position offers the chance to lead projects from concept to production, and shape internal GAI strategy in a collaborative environment.

What you'll do day-to-day

You’ll join a dynamic team, with the potential to:

• Lead and contribute to greenfield projects, driving innovation and defining the future of GAI at the firm through full-cycle ownership, from exploration to deployment.
• Collaborate directly with internal groups and end users to build GAI applications tailored to nuanced, real-world business needs, and deliver solutions with immediate impact.
• Experiment with emerging AI tools and applications, rapidly prototyping and integrating them across platforms to enhance usability and effectiveness firmwide.
• Scale GAI tool adoption and improve integration with internal systems, with a focus on enabling seamless workflows and efficiency gains.

Who we're looking for

• An extensive background in software and product development and a solid understanding of GAI technologies, demonstrated through hands-on experience building and scaling AI solutions at the product or company level.
• Expertise in technical or entrepreneurial environments, with a record of solving complex challenges and taking projects from inception to deployment.
• 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 200,000USD to 250,000USD. 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.

Palo Alto, CA

Position Description: As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture, visualize data, assist with exporting and deploying neural networks to the bot, and evaluate experimental results. You will help us automate the entire workflows of training, validation, and production of the Optimus. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications.

Responsibilities: Build and improve our Python training infrastructure for stable and faster training

Build the tooling and infrastructure for reporting and visualizing model metrics and performance

Build the pipelines to run and validate our PyTorch models

Manage, analyze, and visualize our training and test datasets

Coordinate with the team managing the hardware cluster to maintain high availability / jobs throughput for Machine Learning

Build and improve tooling to deploy trained neural nets to Tesla hardware

Requirements: Practical experience programming in Python and/or C++

Proficient in system-level software, particularly hardware-software interactions and resource utilization

Understanding of modern machine learning concepts and state of the art deep learning

Experience working with training frameworks, ideally PyTorch

Demonstrated experience scaling neural network training jobs across clusters of GPU’s

Optional: Previous experience in deep learning deployment

Optional: Profiling and optimizing CPU-GPU interactions (pipelining compute/transfers, etc)

San Jose, CA, USA

We are seeking a creative and technically skilled Prompt Engineer to enhance large language model (LLM) performance across business-critical workflows. This position centers on designing, testing, and integrating strategies that drive intelligent agents and enterprise use cases. You will work closely with AI engineers, product teams, and domain experts to guarantee scalable, safe, and high-accuracy AI applications.

What you'll Do - Prompt Strategy & Design: Develop templates and multi-step chains tailored to specific business functions (e.g., sales enablement, support, knowledge management). Develop few-shot, zero-shot, and hybrid patterns for enhanced reasoning and context retention. Maintain libraries for reuse and version control.

• Function Calling & Tool Use: Implement LLM function calling to trigger APIs, databases, or internal tools. Build tool-use pipelines within agent workflows for complex task automation.

• Conversation Flow & Persona Design: Define and build agent personas, roles, and behaviors for domain-specific applications. Manage multi-turn conversations, memory handling, and contextual continuity.

• Enterprise-grade Optimization: Tailor prompts for performance in enterprise environments, prioritizing accuracy, privacy, fairness, and compliance. Collaborate with legal and security teams to mitigate hallucination, bias, and misuse risks.

• Testing & Evaluation: Tailor prompts for performance in enterprise environments, prioritizing accuracy, privacy, fairness, and compliance. Collaborate with legal and security teams to mitigate hallucination, bias, and misuse risks.

• Deployment & Integration: Partner with AI Agent Engineers to integrate prompts into agent workflows and orchestration pipelines. Maintain documentation and workflows for deployment in production environments.

What you need to succeed - 3+ years of experience in NLP, AI/ML product development, or application scripting - Strong grasp of LLM capabilities and limitations (e.g., OpenAI, Claude, Mistral, Cohere) - Experience crafting prompts and evaluation methods for enterprise tasks - Familiarity with frameworks like LangChain, Semantic Kernel, or AutoGen - Strong Python and API integration skills - Excellent written communication and structured thinking

Preferred Qualifications - Experience with LLM function calling, custom tool integration, and agent workflows - Background in UX writing, human-computer interaction, or instructional design - Understanding of enterprise compliance (e.g., SOC 2, GDPR) in AI systems - Bachelor's or equivalent experience in Computer Science, Computational Linguistics, Cognitive Science, or a related field

Our 10-week internship is your chance to experience life as a researcher at IMC. You will work alongside your mentor to explore new research ideas and build custom analysis tools that may be deployed into production. Throughout the summer, there will be opportunities to enhance your knowledge of options theory, market making, algorithm complexity and trades analysis. We provide a highly competitive compensation package with accommodations included. The bar for talent at IMC is high and interns who meet our performance expectations will have the opportunity to secure a full time Graduate Researcher position at the end of the program. Where you go from here is up to you!

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.

Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Deep Learning Computer Architecture teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.

Throughout the 12-week minimum full-time internship, students will work on projects that have a measurable impact on our business. We’re looking for students pursuing Bachelor's, Master's, or PhD degree within a relevant or related field.

What we need to see: Must be actively enrolled in a university pursuing a Bachelor's, Master's, or PhD degree in Electrical Engineering, Computer Engineering, or a related field, for the entire duration of the internship.

Course or internship experience related to the following areas could be required:
Computer Architecture experience in one or more of these focus areas: GPU Architecture, CPU Architecture, Deep Learning, GPU Computing, Parallel Programming, or High-Performance Computing Systems  

GPU Computing (CUDA, OpenCL, OpenACC), GPU Memory Systems, Deep Learning Frameworks (PyTorch, TensorFlow, Keras, Caffe), HPC (MPI, OpenMP)
Modelling/Performance Analysis, Parallel Processing, Neural Network Architectures, GPU Acceleration, Deep Learning Neural Networks, Compiler Programming
Performance Modeling, Profiling, Optimizing, and/or Analysis

Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies:
C, C++, Python, Perl, GPU Computing (CUDA, OpenCL, OpenACC), Deep Learning Frameworks (PyTorch, TensorFlow, Caffe), HPC (MPI, OpenMP)

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.

You will also be eligible for Intern benefits. ​

Applications are accepted on an ongoing basis.

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.

Palo Alto, CA

Position Description: Tesla is looking for strong Machine Learning Engineers to help build foundation models for robotics to drive the future of autonomy across all current and future generations of vehicles. You will work on a lean team without boundaries and have access to one of the world’s largest training clusters. Most importantly, you will see your work repeatedly shipped to and utilized by millions of Tesla’s customers.

Responsibilities: Leverage millions of miles of driving data and interventions to build a robust and scalable end-to-end learning based self-driving system Use cutting-edge techniques from generative modeling, imitation learning, and reinforcement learning to improve the planning and reasoning capabilities of our driving models Experiment with data generation and fleet data collection approaches to enhance the diversity and quality of training data Integrate directly with vehicle firmware and ship production quality, safety-critical software to the entirety of Tesla's vehicle fleet

Requirements: Strong experience with Python, any major deep learning framework, and software engineering best practices An "under the hood" knowledge of deep learning modern architectures, optimization, model alignment, etc. Proven expertise in deploying production ML models for self-driving, robotics, or natural language processing at scale Comfort with C++ to help integrate with vehicle firmware and take projects from ideas to shipped products

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.

With more than 600 million users around the world and 400 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

We are seeking talented Staff Machine Learning Engineers for multiple openings across our Core Engineering organization, including teams such as Search, Notifications, and Content & User Engineering. In these roles, you will drive the development of state-of-the-art applied machine learning systems that power core Pinterest experiences.

What you’ll do:

• Design features and build large-scale machine learning models to improve user ads action prediction with low latency
• Develop new techniques for inferring user interests from online and offline activity
• Mine text, visual, and user signals to better understand user intention
• Work with product and sales teams to design and implement new ad products

What we’re looking for:

• Degree in computer science, machine learning, statistics, or related field
• 6+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
• 2+ years of experience leading projects/teams
• Strong mathematical skills with knowledge of statistical methods
• Cross-functional collaborator and strong communicator

Palo Alto

Our formula for success is to hire exceptional people, encourage their ideas and reward their results.

As an AI Research Intern, you will be an integral member of a team of experienced technologists, quantitative researchers, and traders. You will collaborate closely with other researchers to solve challenging AI and machine learning problems. Your projects will vary depending on priorities at the start of your employment and could include solving forecasting problems or developing large language models (LLMs). We are looking for individuals eager to learn new AI technologies, create innovative solutions, and choose the right tools to directly impact our business. You will be surrounded by cutting-edge technology, given immediate responsibility, mentored by industry-leading experts, and attend a robust training program to ensure your success at DRW.

How you will make an impact… Algorithm Development: Creating and testing new AI models and algorithms to solve specific problems or improve existing methods. Data Engineering: Building data pipelines for model training and evaluation, including data collection, cleaning, preprocessing, and labeling, while contributing to better data management practices. Model Testing & Evaluation: Designing and implementing rigorous testing frameworks to assess model performance and identify areas for improvement. Collaboration: Working closely with team members to establish and refine research methodologies, promoting peer reviews, testing, and thorough documentation. Research & Learning: Staying updated on the latest AI techniques and advancements, sharing insights, and actively bringing improvements to research processes.

What you bring to the team… Are pursuing a PhD in artificial intelligence, machine learning, computer science, or a related field graduating between December 2026 and June 2027. Strong foundation in AI concepts. Strong knowledge of machine learning. Solid technical and programming skills (Python, Java, GitHub). Familiarity with machine learning framework (Spark, PyTorch, etc.). Excellent analytical, problem-solving, and communication skills. Deep interest in financial markets.

Preferred Skills: Experience with NLP tasks Knowledge of TensorFlow or PyTorch. Basic understanding of MLOps principles (monitoring, versioning, model serving).

Learning Opportunities: Gain in-depth experience with cutting-edge ML/AI techniques and model deployment. Develop robust machine learning research skills, from data engineering to model evaluation, while contributing to advancements in AI methodologies and practices. Contribute to research projects with potential impact on financial decision-making and other applied domains. Engage in fostering a collaborative research culture, driving improvements in research quality, and interdisciplinary collaboration.

What to expect during the internship Meaningful projects: Each project, advised by a trader, promotes a comprehensive learning experience and provides you with real-world work experience. Community: Throughout the summer, we host a variety of educational, social and team-building activities to explore the city, foster friendships and camaraderie. Housing: DRW provides fully furnished apartments located close to the office – making your morning commute as easy as possible. Mentorship: You’ll build a professional relationship with an experienced mentor in your field. Mentors and mentees meet to discuss goals, challenges and professional development and explore the city together at our mentor outings. Education: As the trading industry continually evolves, both in terms of new products and transaction methods, the future will present us with unique opportunities and challenges. You’ll complete an options course taught by an experienced trader and participate in a technology immersion course to better understand how technology and trading intersect.