Data & ML Ops Lead

About the role

As the MLOps Lead, you will drive the strategy, technical roadmap, and leadership of the MLOps team to support the full ML lifecycle. You will serve as both a technical lead and people manager, responsible for building, mentoring, and scaling a high-performing engineering team. Your work will enable high-velocity and high-quality ML development and deployment across the organization.

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
• Data pipelines
• 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. The company began as an ETH Zurich spin-out and is currently deployed across multiple countries with leading construction and equipment partners.