Description Our client has built and published award-winning research on the frontier of AI.

They have built and worked on deep learning, reinforcement learning, multi-agent systems, economics, robotics, automated experiment design, program synthesis, formal verification, and more.

Their mission is to build intelligence to co-invent the future.

They envision a future where people and powerful AI agents interact and collaborate in unseen ways to create and discover.

To achieve this, they build AI that plans, abstracts, verifies, and discovers new skills and knowledge.

They are backed by top-tier investors and partners including Eric Schmidt (former CEO of Google and former Executive Chairman of Alphabet), Caltech, Jeff Dean (Chief Scientist, Google DeepMind and Google Research), and JP Millon. Key Responsibilities Be a key team member that will help set the course, take ownership, and execute rapidly. Design, train, and evaluate hybrid AI systems that perform well at scale and make optimal trade-offs. Build data processing pipelines Implement machine learning models Run machine learning workloads at scale using distributed computing Define and apply simple design principles that scale (Occam's Razor) Solve min-max problems: how can we do more with less? Accelerate our work by removing operational and tooling bottlenecks. Skills, Knowledge and Expertise You enjoy and are energized by solving challenging and meaningful real-world problems. You have a track record in a technical domain, e.g., machine learning, computer science, physics, math. You have developed and implemented machine learning algorithms, models, and tools. You have strong programming (Python, C++) and math abilities. You have clear verbal and written communication skills You have strong conceptual and structured thinking. You are willing and able to learn quickly. You have team spirit. You can independently structure, plan, prioritize, and get things done. You have a drive for excellence, a sense of urgency, and bias to action. Open-source projects, published research papers, or other examples of experience in using machine learning. Experience with applying deep learning, reinforcement learning, unsupervised learning, and other techniques to large-scale problems. Experience with distributed computing and handling large datasets. Benefits Competitive salary Stock options 100% covered premium health, dental, and vision insurance. Wellness benefits (e.g., gym, fitness classes, physical therapy). Retirement 401k: 100% match of your 401k deferrals up to 4% of your compensation. Commuter benefits Daily meals in the office Training and development budget, e.g., for domestic conferences. Flexible working hours Unlimited PTO (with manager approval) Team-building events and celebrations

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Machine Learning Engineer