Machine Learning Engineer

Overview

As a Machine Learning Engineer in a fast-moving startup, you will own production ML systems that accelerate IC verification. You work closely with researchers and customers to deliver data-driven models from ingestion to deployment, improving tapeout safety. You’ll shape tooling and APIs, enabling scalable ML solutions inside production chip-design workflows. This role offers hands-on impact in a silicon-focused domain with strong collaboration and learning opportunities.

Pay / Benefits

• competitive salary
• bonus
• equity
• flexible remote/hybrid
• learning and development support
• exposure to real customer workflows

Responsibilities

• own end-to-end ML systems from data ingestion to deployment
• build and maintain data pipelines for complex scientific datasets
• develop production-ready models using Python and ML frameworks
• design clear specs and APIs, and document for customers
• contribute to testing, CI/CD, and code quality
• collaborate with researchers and translate customer workflows into solutions
• work with customers to demonstrate and iterate on ML capabilities

Key requirements

• 3+ years in industry building production ML systems
• First degree in a relevant STEM subject
• Python + PyTorch/JAX expertise for training, inference, and model export
• Experience building data pipelines for complex scientific/engineering datasets
• Solid software engineering fundamentals — testing, CI/CD, clean APIs
• End‑to‑end ML system ownership from data ingestion to model deployment
• Clear communication — writing specs, documenting APIs, presenting to customers

• clear communication
• collaboration with cross-functional teams
• customer-facing communication
• Python
• PyTorch/JAX
• data pipelines for scientific datasets

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