Data & ML Ops Lead

Job summary

The MLOps Lead is responsible for driving the strategy and technical roadmap of the MLOps team, ensuring the development and operation of systems that support the full ML lifecycle. Key responsibilities include building high-throughput data ingestion pipelines for multimodal datasets, leading the deployment and monitoring of ML models across edge devices, and establishing robust model lifecycle management practices.

Qualifications

• 7+ years of hands-on experience in ML Ops, data engineering, or ML infrastructure roles
• 5+ years of production experience with Kubernetes
• Prior experience in technical leadership or engineering management
• Strong background in building, scaling, and optimizing large-scale data pipeline infrastructure
• Proven experience deploying, observing, and maintaining ML models at scale

Responsibilities

• Own the MLOps technical vision and roadmap
• Lead and build an engineering team to architect, build, and optimize high-throughput data ingestion pipelines
• Design, build, and operate high-availability hybrid compute clusters
• Lead the continuous deployment and monitoring pipelines for ML models
• Establish full model lifecycle management
• Collaborate closely with robotics engineers

Skills

Degrees

Relocation