Lead MLOps Engineer
Core
Lead the MLOps technical direction and platform roadmap to move machine learning from experimentation into reliable, scalable production for AI-driven infrastructure and building design.
Role type
Senior hands-on IC Lead MLOps Engineer
Builds
Production ML infrastructure for training, deployment, serving, and monitoring at scale
Domain
AI for Engineering / Infrastructure & Buildings
Deliverable
production ML models
Required skills
MLOps platform ownership, ML pipeline architecture, Python, FastAPI/Flask/Django, Docker, CI/CD, Azure cloud, reliability engineering, observability, architecture decision-making
Preferred skills
Kubernetes, Terraform, MLflow/Weights & Biases, Prometheus/Grafana/ELK/OpenTelemetry, distributed ML workloads, GPU infrastructure, LLMOps, generative AI, reinforcement learning
Responsibilities
Define MLOps technical vision and engineering standards; architect and own production ML infrastructure; provide technical leadership and mentoring; build Python services and platform tooling; ensure reliability, security, and cost efficiency; lead technical response to complex production issues; align cross-functional teams on priorities
Seniority
Senior, hands-on IC with leadership responsibilities
