Machine Learning Engineer

Apiphany is a pioneering foundational AI company for physical product development. We empower global innovators in automotive, aerospace, medtech, and energy to transform mountains of unstructured technical data into real-time, actionable insights. Backed by world-class investors from Markforged, Databricks, GM, and Character, our mission is to revolutionize how engineering decisions are made, turning complexity into clarity for the world’s top manufacturers.

Our models are built for the complexities of engineering and manufacturing. Our models understand physics principles, design specifications, and program constraints. We’re a small, elite team of builders from Stanford, Berkeley, MIT, UW, and CMU, alongside industry leaders from GM, Ford, and Genesis Therapeutics. We’re passionate about transforming hard-tech and building a category-defining company together.

As a ML Engineer at Apiphany, you’ll develop and implement advanced machine learning models to tackle some of the hardest problems in the physical world. You’ll design systems that can reason about complex engineering data and build AI that understands physics, design constraints, and real-world performance tradeoffs.

This is a role for builders who want to push the frontier of what AI can do in the physical world.

• Expert-level programming skills in Python

• Solid understanding of deep learning and its applications in natural language processing (NLP)

• Deep understanding of large language models (LLMs)

• Exceptional problem-solving skills and a passion for pushing the boundaries of AI technology.

• Background in competitive programming.

• Contributions to open-source initiatives.

• Startup mindset: bias toward action, rapid iteration, and ownership

• Mission-driven and customer-obsessed

• Self-motivated, collaborative, and eager to raise the bar for the whole team

• Passion for building in a fast-paced, hyper-growth startup environment.

• Base Salary: $110,000–$170,000

• Equity: Generous Equity

• Visa Sponsorship

• Hybrid work: 3 days in San Francisco office

• 401(k) plan

• Medical, Dental, and Vision insurance coverage

• Snacks at the office

• Paid Time Off (PTO): Flexible vacation policy