Data & ML Ops Lead

About the role

Gravis Robotics is seeking an MLOps Lead to drive the strategy and technical roadmap for their machine learning infrastructure. You will lead and mentor a high-performing engineering team to build and scale systems that support the full ML lifecycle, from edge data ingestion to model deployment at scale. This role involves collaborating with robotics leadership to enable high-velocity ML development for autonomous construction machinery.

Responsibilities

• Own the MLOps technical vision and roadmap, aligning infrastructure investments and architecture decisions with broader company and engineering milestones
• Lead and build an engineering team to architect, build, and optimize high-throughput data ingestion pipelines and platform infrastructure for petabyte-scale multimodal datasets
• Mentor and grow the team members through continuous feedback, career development, and technical guidance
• Design, build, and operate high-availability hybrid compute clusters, providing developers and researchers with a seamless, unified compute experience
• Lead the continuous deployment and monitoring pipelines for ML models deployed across thousands of edge devices in the field
• Establish full model lifecycle management, incorporating robust model registries, artifact versioning, automated regression testing, and real-time observability/monitoring
• Collaborate closely with robotics engineers to understand requirements and translate them into reliable, scalable training environments
• Evaluate and integrate best-in-class MLOps tooling on cloud and on-prem compute platforms

Required skills

• MLOps
• Data engineering
• ML infrastructure
• Kubernetes
• AWS
• GCP
• Azure
• CI/CD
• Infrastructure as Code
• MLflow
• W&B
• DVC

Nice to have

• Robotics data
• Foxglove
• Prometheus
• Grafana
• Database architectures

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or a related field

About the Company

Gravis Robotics is a high-growth Series A start-up backed by SoftBank, bringing Physical AI to the construction industry by turning heavy construction machines into autonomous robots. Originally an ETH Zurich spin-out, the company develops machine-agnostic retrofit kits that add autonomy to excavators and wheel loaders.