Senior AI Application Engineer

About SF MOTORS, INC. (dba SERES)

SF Motors is building the next generation of intelligent robotic systems that combine advanced mobility, autonomy, and human-like adaptability. Our mission is to revolutionize how machines move, perceive, and interact in complex environments by integrating control engineering, artificial intelligence, and machine learning at every level of design.

Job Title: Sr. AI Application Engineer – Machine Learning, Agentic AI & Physics AI

Location: Milpitas

Department: Advanced Engineering / AI Applications

Position Overview

We are seeking an Sr. AI Application Engineer to develop and deploy advanced AI systems that bridge data-driven intelligence with real-world engineering. The ideal candidate will have a strong foundation in machine learning, agentic AI, and physics-informed modeling, and will apply these techniques to complex engineering problems such as multi-objective design optimization, AI model fine-tuning, simulation acceleration, and autonomous decision-making systems.

This role requires both theoretical depth in AI/ML algorithms and practical engineering insight to create robust, deployable solutions in domains such as mechanical, electrical, aerospace, or materials engineering.

Key Responsibilities

• AI Model Development & Optimization
• 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).
• Agentic AI & Autonomous Systems
• 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.
• Apply reinforcement learning or control-oriented AI for adaptive engineering systems.
• AI Deployment & Integration
• 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.
• Integrate AI systems into engineering tools and environments (e.g., CAD/CAE software, simulation platforms, or digital twins).
• Research & Innovation
• Explore novel applications of physics-based AI, agentic reasoning, and self-improving systems within engineering contexts.
• Stay current with advancements in foundation models, multi-modal AI, and generative design.
• Contribute to white papers, patents, and internal R&D initiatives.
• Collaboration & Communication
• Work closely with domain engineers, data scientists, and software developers to translate engineering challenges into AI-driven solutions.
• Communicate complex technical concepts to multidisciplinary teams and stakeholders.

Required Qualifications

• Education:
• 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.
• Technical Expertise:
• 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).
• Soft Skills:
• Strong analytical thinking, problem-solving, and communication skills.
• Ability to work in multidisciplinary teams and adapt to evolving technologies.

Preferred Qualifications

• Experience with reinforcement learning, evolutionary algorithms, or active learning for design optimization.
• Background in multi-physics simulation (CFD, FEA, thermal, or electromagnetics).
• Prior exposure to generative AI for engineering design or AI-driven control systems.
• Familiarity with digital twins and real-time sensor integration.
• Publications or patents in AI for engineering or computational sciences.

Why Join Us

• Work at the frontier of AI-driven engineering innovation.
• Collaborate with experts across AI, physics, and engineering disciplines.
• Influence how next-generation products are designed, optimized, and deployed through intelligent systems.
• Competitive salary, benefits, and opportunities for research and publication.
• High ownership & impact: Play a key role in a small, fast-moving team where your work directly shapes the product.
• Full-stack robotics exposure: Work across system, software, and AI — not limited to a narrow role.
• Collaborative culture: Join an open, innovative environment that values ideas and initiative.
• Rapid growth: Accelerate your learning curve with opportunities for professional and personal development.
• Future-focused: Help shape the next generation of real-world robotics applications.
• Competitive benefits: Attractive package including Medical, Dental, Vision, 401K match, free lunch and more.

Candidates must be legally authorized to work in the United States and verification of employment authorization will be required at the time of hire.

SERES is an equal opportunity employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.