Robotic AI Engineer/Applied Scientist - Foundation Models

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{
  "title": "Robotic AI Engineer/Applied Scientist - Foundation Models",
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      "name": "San Francisco Bay Area",
      "location": "California, United States",
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  "location": {
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      "name": "Work Arrangement",
      "value": "On-site",
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      "name": "Team",
      "value": "Artificial intelligence engineering",
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      "name": "Job Exemptions",
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      "id": 5149277008,
      "name": "Job Description",
      "value": "We are seeking an exceptional AI Foundation Model Engineer to design, implement, test, and deploy state-of-the-art foundation models on our robots.\n\nIn this role, you will:\n\n- Develop, fine-tune, and optimize foundation models for the robot, leveraging advanced techniques such as pretraining, fine-tuning, and retrieval-augmented generation (RAG).\n- Translate high-level application goals into foundational AI solutions, delivering robust and scalable models that perform effectively in real-world scenarios.\n- Build pipelines for training, evaluation, and deployment of models on various platforms, ensuring high performance and adaptability across diverse use cases.\n- Stay at the forefront of research, incorporating cutting-edge advancements in AI and foundation models to enhance system capabilities and push technical boundaries.\n- Own critical projects end-to-end, from model design and experimentation to deployment and continuous improvement.\n- Collaborate with cross-functional teams, including data, software, and systems engineers, to integrate models seamlessly into production workflows.",
      "value_type": "long_text"
    },
    {
      "id": 5187056008,
      "name": "Job Description Summary",
      "value": "Develop and implement foundation models for robots",
      "value_type": "short_text"
    },
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      "id": 5149278008,
      "name": "Job Qualifications",
      "value": "Must-have:\n- MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.\n- Deep understanding of machine learning concepts, including attention mechanisms, transformers, and training techniques\n- Experience working with fine-tuning, retrieval-augmented generation (RAG), prompt engineering, or reinforcement learning with human feedback (RLHF).\n- Proficiency in programming languages and tools commonly used in machine learning (e.g. Python).\n- A strong grasp of theoretical concepts and practical implementation of multimodal foundation models.\n\nNice-to-have:\n- Experience with deployment of models to edge devices for real-time inference.\n- Experience with large-scale distributed training and optimization frameworks (e.g. PyTorch, TensorFlow) and familiarity with tools for model compression and quantization\n- General knowledge of robotics principles, including kinematics, dynamics, and control.\n- Publications or contributions to the machine learning community, particularly in areas related to robotics or large language models.\n- Excellent problem-solving skills, with the ability to innovate and experiment with novel approaches",
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  "updated_at": "2026-04-20T17:32:50-04:00",
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      "name": "Engineering",
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  "company_name": "Maven Robotics",
  "requisition_id": 4127973008,
  "first_published": "2025-01-09T14:32:44-05:00",
  "application_deadline": null
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