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.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, 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 Ads Delivery team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. We are looking for a Machine Learning Engineer/Economist with a strong theoretical and data analysis background that understands market design concepts and has the engineering skills to bring them to market. We are looking for an economist who can get their hands dirty and work side by side with other engineers, to advance the efficiency of the Pinterest Marketplace. The nature of projects within this team require a deep understanding of trade-offs, founded on both economic theory and data analysis, from the ideation phase all the way to launch review.

What you’ll do:

• Build statistical models and production systems to improve marketplace design and operations for Pinners, Partners, and Pinterest.
• Tune marketplace parameters (e.g., utility function), optimize ad diversity and load, implement auctions, and model long‑term effects to reduce ad fatigue and improve advertiser outcomes.
• Define and implement experiments to understand long term Marketplace effects.
• Develop strategies to balance long and short term business objectives.
• Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.
• Work across application areas such as marketplace performance analysis, advertiser churn/retention modeling, promotional bandwidth allocation, ranking/pricing/mechanism design, bidding/budgeting innovation, and anticipating second‑order effects for new ad offerings.

What we’re looking for:

• Degree in Computer Science, Machine Learning, Economics, Operations Research, Statistics or a related field.
• Industry experience in applying economics or machine learning to real products (e.g., ads auctions, pricing, marketplaces, or large‑scale recommendation/search systems).
• Knowledge in auction theory, market design, and econometrics with excellent data analysis skills.
• Strong software engineering and mathematical skills and proficiency with statistical methods.
• Experience with online experimentation and causal inference (A/B testing, long‑running experiments, or similar) in large‑scale systems.
• Practical understanding of machine learning algorithms and techniques.
• Impact‑driven, highly collaborative, and an effective communicator; prior ads or two‑sided marketplace experience strongly preferred.

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).

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.

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.

We are looking for a Principal Machine Learning Engineer, a senior technical visionary, to be the Principal Technical Lead for our Content Engineering team setting up overall technical strategy, unified technical architecture and defining a roadmap for industry‑leading methodology. Strong hands-on machine learning background including deep learning architectures, generative AI, low-resource ML (zero shot, few shot), responsible AI and large scale deployment and measurement is required.

As the Principal Tech Lead for Content you'll be responsible for the technical direction, strategy and health of our Content Engineering org. You'll ensure that our technology can deliver on the business/product requirements necessary to keep Pinterest safe and positive. This means working with other leads to set and execute a long-term strategy for Trust, aligning the strategy with other clients where it makes sense and communicating to leadership our current status and path to having world-class Trust capabilities. You'll also foster a healthy community where all Trust engineers can learn best practices, collaborate effectively and understand our technical direction.

What you’ll do

• Develop strong partnerships with product teams to understand and proactively address future technology needs and current developer pain points.
• Champion and drive large-scale, cross-functional initiatives that improve the trust and safety of our platform.
• Act as the ultimate “customer representative” for engineers on Trust, including representing needs to leadership and prioritizing projects on the platform teams that ensure high quality capabilities and a world-class Pinner experience.
• Scale your leadership through both direct mentorship and via best practices, processes, training and tools.
• Ensure solid technical plans are in place for projects within Trust via direct review or delegation.
• Be the technical point of contact for decisions that impact the whole Pinterest platform and for cross-functional partners like policy, operations and legal.

What we’re looking for:

• Deep expertise building large scale ML systems at scale with modern frameworks.
• Knowledge of (and a passion for) building responsible and quality‑first discovery surfaces.
• Track record of delivering large, cross-functional projects across multiple organizations.
• Strong written and verbal communication skills and proven ability to collaborate cross-functionally.

AI Scientist - Formal methods for science

Position overview:

As an AI Research Scientist with focus on formal methods for science, you will join a focused team, playing a key role in building new formal verification tools for science and engineering. Your responsibilities will include developing AI tools that will enable the systematic adoption of formal methods in quantitative scientific fields such as physics and engineering. You will also manage data curation, conduct benchmarking to evaluate performance, analyze reasoning flaws and propose solutions. Close collaboration with our dedicated cross-functional team - consisting of Mathematicians, AI Engineers, Software Engineers, Lean4 developers, Physicists and AI scientists - will be essential to the success of the project.

Your mission:

• Project contribution and technical execution: Play an active role in designing and developing autoformalization and validation strategies specifically tailored for scientific applications.

• Solution design & implementation: Engage in hands-on development to drive shorter-term impactful solutions in collaboration with our Business Development team. Propose, discuss, and implement technical solutions that address complex challenges, ensuring they are are well-structured, efficient, and aligned with industry best practices.

• Innovation & continuous learning: Stay updated with state-of-the-art techniques and advancements in the field. Continuously integrate the latest research and technologies to enhance the products’ impact.

• Cross-team collaboration: Work closely with AI and development teams to ensure seamless integration of solutions. Promote open communication and cooperation to enhance productivity and technical excellence.

• Knowledge sharing and developing the team: Foster a collaborative culture by actively sharing knowledge, insights, and best practices. Encourage teamwork and continuous learning to strengthen overall expertise within the company.

Key requirements:

• PhD in Computer Science, Artificial Intelligence, Physics, Machine Learning for scientific applications or related fields.
• Experience in applications of machine learning to relevant projects
• Proficient in Python, with the ability to write clean and efficient code
• Experienced with agentic AI and major deep learning framework
• Solid understanding of statistics and probability

About you:

• You excel as a team player, thriving in multidisciplinary and multicultural environments.
• You are highly motivated, hard-working, and committed to personal and professional growth through constant learning, new challenges and advancements.
• You quickly grasp new concepts and technologies, adapting efficiently to evolving requirements.
• You have a real passion for science and maths, and have a deep curiosity for understanding concepts from first principles.
• You like to try new technologies and quickly build exploratory prototypes.
• You thrive in a dynamic, fast-paced environment, embracing change with a proactive and solution-oriented approach.

Nice to have:

• Background in Physics, Engineering or other related computational science.
• Publications relevant to the company domain at top-tier conferences.
• Internship or work experience in one top AI company.
• Strong experience in at least one of the following: reinforcement learning, representation learning, program synthesis, NLP, graph machine learning, knowledge graphs, applied machine learning and data mining, optimization, machine learning for theorem proving, agentic LLMs and RAG, machine learning for science
• Proven contribution to open source projects.

Remote - Americas

Applied Machine Learning Engineer - Search

Every day, millions of people search for products across Shopify's ecosystem. That's not just queries—that's dreams, businesses, and livelihoods riding on whether someone finds the perfect vintage jacket or the exact drill bit they need. As a Machine Learning Engineer specializing in Search Recommendations, you'll be the one making that magic happen. With a search index unifying over a billion products, you're tackling one of the hardest search problems at unprecedented scale. We're building cutting-edge product search from the ground up using the latest LLM advances and vector matching technologies to create search experiences that truly understand what people are looking for.

Key Responsibilities:

• Design and implement AI-powered features to enhance search recommendations and personalization
• Collaborate with data scientists and engineers to productionize data products through rigorous experimentation and metrics analysis
• Build and maintain robust, scalable data pipelines for search and recommendation systems
• Develop comprehensive tools for evaluation and relevance engineering, following high-quality software engineering practices
• Mentor engineers and data scientists while fostering a culture of innovation and technical excellence

Qualifications:

• Expertise in relevance engineering and recommendation systems, with hands-on experience in Elasticsearch, Solr, or vector databases
• Strong proficiency in Python with solid object-oriented programming skills
• Proven ability to write optimized, low-latency code for high-performance systems
• Experience deploying machine learning, NLP, or generative AI products at scale (strong plus)
• Familiarity with statistical methods and exposure to Ruby, Rails, or Rust (advantageous)
• Track record of shipping ML solutions that real users depend on

This role may require on-call work

Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.


At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.


Various locations available

Adobe Researchers are developing the next generation of advanced technologies and user experiences, inventing a future where Adobe enables new forms of creativity, frees people from routine tasks, and allows enterprises to understand and act quickly on customer and business insights. Our research labs are actively published in leading journals and conferences, work with product teams on high profile features, and explore new product opportunities across various domains. We are especially interested in fostering ongoing collaborations that last beyond the internship and become part of your PhD thesis.

Adobe Research focuses on the following research areas: - Content Intelligence - AI & Machine Learning - Computer Graphics (2D&3D) - Data Intelligence - Computer Vision, Imaging & Video - Audio - Systems and Languages - Natural Language Processing - Human Computer Interaction - AR, VR & 360 Photography - Document Intelligence - Intelligent Agents & Assistants

What you will do

Under the direction of an Adobe Research mentor, you will: - Pursue a research problem to apply to Adobe’s products and with the possibility of academic publication - Develop new algorithms, run experiments, and produce demonstration prototypes - Document and present your work, both verbally and in writing

What you will need - Current PhD or master's student in computer science, or related field (exceptional undergraduates will also be considered) - Sufficient research skills and background in your chosen subject area - Strong communication skills and teamwork experience - Passion for solving real-world problems with web-scale data using and inventing innovative Machine Learning algorithms.

Waddle Labs: - we are an early-stage startup - we build robotics models to solve physical bottlenecks in science (eg. wet lab experiments) - YC W26

The other companies on this career site know what they're doing. We don't. Do you want to help us figure it out?

If you want to find out more, reach out to wave@waddlelabs.ai with 1 sentence about what you’re interested in.

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.

At Pinterest Labs, you'll join a world-class team of research scientists and machine learning engineers to tackle cutting-edge challenges in machine learning and artificial intelligence. This role places you at the intersection of applied research and scalable infrastructure, focusing heavily on ML framework and efficiency.

You will conduct research that can be applied across Pinterest engineering teams, engaging in external collaborations and mentoring. Your research focus will specifically target ML efficiency and large-scale infrastructure challenges within high-impact areas such as: generative recommender systems, post-training, reinforcement learning, multi-modality representation learning, and graph neural networks.

What you’ll do:

• Design, develop, maintain, and enhance advanced machine learning solutions across various key business areas.
• Lead the technical strategy for optimizing and improving the efficiency of large-scale ML infrastructure.
• Lead high-impact machine learning projects, overseeing priorities, deadlines, and deliverables while providing technical guidance.
• Drive alignment and clarity on goals, outcomes, and timelines across teams.

What we’re looking for:

• MS/PhD in Computer Science or a related field degree.
• 10+ years of industry experience.
• Experience in distributed systems, ML frameworks (e.g. PyTorch), and scaling laws.
• Experience in research and in solving analytical problems.
• Cross-functional collaborator and strong communicator.
• Comfortable solving ambiguous problems and adapting to a dynamic environment.