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Data & ML Ops Lead

GRAVIS ROBOTICS· Platform
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Hybrid (Zurich)Full-timePosted 3w ago

About the role

Gravis Robotics is hiring a Data & ML Ops Lead to own and execute the MLOps strategy, architecture, and team leadership for scalable ML pipelines and production deployments across edge devices, on-premise and cloud infrastructure.

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 (e.g., LiDAR point clouds, camera streams, GNSS/IMU, hydraulics time-series)
  • Mentor and grow the team members through continuous feedback, career development, and technical guidance
  • Design, build, and operate high-availability hybrid (cloud and on-premise) 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

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or a related field
  • 7+ years of hands-on experience in ML Ops, data engineering, or ML infrastructure roles, preferably in a leadership role driving the ML Infrastructure
  • 5+ years of production experience with Kubernetes, including designing and maintaining cloud infrastructure (AWS, GCP, or Azure) and on-premise cluster infrastructure
  • Prior experience in technical leadership or engineering management, including mentoring and growing engineers
  • Strong background in building, scaling, and optimizing large-scale data pipeline infrastructure for ingesting complex multimodal datasets and high-volume data and organizing them in curated datasets (e.g. using Encord, Scale AI, Lightly)
  • Proven experience deploying, observing, and maintaining ML models at scale across thousands of edge/remote devices in production.
  • Deep experience with model registry, artifact versioning, experiment tracking, and data versioning tools (e.g., MLflow, W&B, DVC)
  • Demonstrated track record of building CI/CD pipelines for ML workloads (e.g., GitHub Actions, GitLab CI) implemented with Infrastructure as Code

Skills

Required:MLOps leadership and strategyKubernetesCloud platformsData pipelinesModel lifecycle managementCI/CD for MLLeadership / people management

Benefits

  • Gravis is committed to an inclusive and diverse workplace
Last updated Oct 21, 2026. Interested? Apply on the company site.

About GRAVIS ROBOTICS

Heavy machinery, automated.

With over a decade of experience in construction robotics, our team has developed the world's most advanced robotic excavators.

automationteleoperationexcavatorsrobots
Company profileWebsite

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