Lead Data Scientist

Quick Facts

• Own the architecture and technical direction for applied AI/ML and agentic AI systems.
• Design and deliver end-to-end ML systems for production use.

Description

You will lead the architecture and drive delivery of applied AI, machine learning, and agentic AI systems that engineers rely on daily. You will take vague, high-impact problems and translate them into designs, plans, and working software, including data pipelines, model development, evaluation, inference services, and monitoring. You will provide direction, review technical designs, and mentor engineers while digging into hard code-level issues when needed.

Responsibilities

• Set the architecture and technical direction for applied AI, ML, and agentic AI work.
• Design end-to-end systems: data pipelines, features, model development, evaluation, inference services, and monitoring.
• Build models used for semiconductor prediction, diagnosis, optimization, and decision support.
• Ship agentic AI for engineering analysis, knowledge retrieval, workflow automation, and decision support; define guardrails and evaluations to build trust.
• Break broad challenges into roadmaps, turning points, and success criteria; report progress, risks, and model limits.

Requirements

• Bachelor’s degree in a related technical field.
• 8+ years of relevant experience.
• Experience leading complex AI/ML/data science or software engineering programs as a technical lead.
• Hands-on supervised learning and statistical modeling experience (feature engineering, validation, evaluation, understanding model behavior).
• Python fluency and experience with PyTorch/TensorFlow/scikit-learn/XGBoost.
• Proven production deployment of ML models, including inference pipelines, APIs, CI/CD, and monitoring.

Benefits

• Choice of medical, dental, and vision plans.
• Programs to protect income during illness or injury, plus paid family leave.
• Robust paid time-off program and paid holidays.
• Additional compensation may include bonuses and equity.