p>Our founding team comes from the AI labs at Stanford and Carnegie Mellon and our board of directors include famed robotics and AI legends including Fei-Fei Li (Chief Scientist of AI at Google and Director of Stanford’s AI Lab), Marc Raibert (founder of Boston Dynamics), and Sebastian Thrun (founder of GoogleX, Waymo; Stanford Professor and considered the father of autonomous vehicles). About Nimble
Nimble is an AI robotics company building the autonomous supply chain to power fast, efficient and economical commerce.
Mountain View, CA30+ days ago
At Google DeepMind, were a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence and ultimately achieve Artificial General Intelligence. We are seeking strong Research Scientists with expertise in AI research and experience in interdisciplinary sociotechnical modeling to join a multimodal safety research effort within Google DeepMinds Frontier AI unit.
Sunnyvale, CA30+ days ago
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. Take ownership of AI quality for production systems by defining technical metrics aligned with business goals, implementing evaluation frameworks, designing experiments, analyzing loss patterns, and driving improvements through system changes or training data enhancements.
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you"ll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you"ll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
Mountain View, CA30+ days ago
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you"ll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
Sunnyvale, CA30+ days ago
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine and deep learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, youll also actively contribute to the wider research community by sharing and publishing your findings with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
Mountain View, CA30+ days ago
From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you"ll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
MongoDB's unified database platform-the most widely available, globally distributed database on the market-helps organizations modernize legacy workloads, embrace innovation, and unleash AI. With offices worldwide and nearly 60,000 customers-including 75% of the Fortune 100 and AI-native startups-relying on MongoDB for their most important applications, we're powering the next era of software.
Palo Alto, CA30+ days ago
MongoDBs unified database platformthe most widely available, globally distributed database on the markethelps organizations modernize legacy workloads, embrace innovation, and unleash AI. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models.
Santa Clara, CA30+ days ago
li>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.
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.
San Francisco, CA26 days ago
Research and implement reinforcement learning techniques - including GRPO, RLHF, RLAIF, DPO, and reward modeling - and translate them into data products (preference datasets, reward signals, verifiable rewards) that customers can use to train and fine-tune large language models. Stay current with the latest developments in large-scale muli-node LLM training, alignment research, and scalable RL methods (on complex environments such as Terminal-Bench), bringing relevant advances into Snorkel''s data-as-a-service approach.
San Francisco, CA30+ days ago
Whether you're looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you're fully supported in building your career in an environment designed for growth, learning, and shared success. D. in machine learning or a related field with a strong publication record is preferred, but we also welcome applications from those with equivalent expertise gained through industry experience, research labs, or other career paths.
Santa Clara, CA30+ days ago
p>What youll be doing: • Driving new abilities into the model • Improving generalization of existing functionalities by understanding weak points, designing a data synthesiis solution, and retraining models • Developing recipes for training models that mix multiple modalities together, such as text, image, video, audio, etc … • Designing solutions that improve pareto efficiency • Collaborating with researchers to translate cutting-edge ideas into production-ready implementations • Exploring new paradigms for evaluation • Demonstrating strong engineering practices, and contributing to open-source communities.
Ways to stand out from the crowd:
• Specific multi-modal LLM research experience • Experience developing and scaling large distributed systems for deep learning • Contributions to open-source LLM systems or large-scale AI infrastructure.
Santa Clara, CA30+ days ago
p>What we need to see: PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience), with 3+ years of post-PhD research experience and a strong record of impactful publications in top circuit, architecture, EDA, or AI/ML venues; with a proven ability to set research direction and translate ideas into tools or products.
Leadership & Collaboration: experience in leading research projects or teams, with a track record of mentoring junior scientists or interns, driving cross-functional initiatives with circuits/VLSI/architecture groups, and fostering collaborations with academia or industry.