SF Motors (dba SERES) is looking to solve complex engineering problems by integrating advanced AI systems, including machine learning, agentic AI, and physics-informed modeling, to revolutionize how machines move, perceive, and interact in complex environments.
Requirements
- Strong proficiency in Python, and familiarity with PyTorch, TensorFlow, or JAX.
- Experience with machine learning algorithms, deep learning architectures, and optimization methods.
- Solid background in numerical methods, physics simulation, or computational modeling.
- Familiarity with agent frameworks (e.g., LangChain, AutoGen, CrewAI, OpenDevin, or custom LLM orchestration systems).
- Proficiency in MLOps, data pipelines, and AI deployment on cloud or edge infrastructure (AWS, Azure, GCP).
- Experience with reinforcement learning, evolutionary algorithms, or active learning for design optimization.
- Background in multi-physics simulation (CFD, FEA, thermal, or electromagnetics).
Responsibilities
- Design, train, and fine-tune machine learning and deep learning models for engineering applications.
- Implement physics-informed neural networks (PINNs), surrogate modeling, or hybrid AI-physics systems.
- Develop and apply multi-objective optimization algorithms (e.g., genetic algorithms, reinforcement learning, Bayesian optimization).
- Build and integrate AI agents capable of autonomous reasoning, decision-making, and goal-directed task execution in engineering workflows.
- Employ agentic architectures (e.g., multi-agent systems, LLM-based reasoning agents) for simulation orchestration and design automation.
- Implement scalable inference pipelines for real-time or batch processing in production environments (cloud or edge).
- Collaborate with DevOps/MLOps teams to deploy AI models using frameworks like TensorFlow Serving, TorchServe, ONNX, or NVIDIA Triton.
Other
- M.S. degree with 5+ years of industry experience, or Ph.D. degree with 3+ years of relevant experience, in Artificial Intelligence, Computer Science, Electrical or Mechanical Engineering, Applied Physics, or a related field.
- Strong analytical thinking, problem-solving, and communication skills.
- Ability to work in multidisciplinary teams and adapt to evolving technologies.
- Candidates must be legally authorized to work in the United States and verification of employment authorization will be required at the time of hire.
- Work at the frontier of AI-driven engineering innovation.
