Data & ML Ops Lead

About the role

Gravis Robotics is building autonomous construction machines and needs a senior leader to own the end‑to‑end MLOps platform that powers its fleet. You will define the technical vision, build a high‑performing team, and ensure reliable data ingestion, model training, and deployment at petabyte scale.

Key responsibilities

• Define and execute the MLOps roadmap, aligning infrastructure investments with company milestones.
• Recruit, mentor, and grow an engineering team that designs high‑throughput data pipelines for multimodal sensor streams (LiDAR, camera, GNSS, hydraulics).
• Architect and operate hybrid cloud/on‑premise compute clusters that provide a seamless experience for researchers and developers.
• Implement continuous deployment, monitoring, and observability for models running on thousands of edge devices.
• Establish model lifecycle management including registries, artifact versioning, automated testing, and real‑time monitoring.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Electrical Engineering or related field.
• 7+ years of hands‑on experience in MLOps, data engineering or ML infrastructure, with at least 5 years in production environments.
• Proven technical leadership experience building and scaling engineering teams.
• Deep expertise in large‑scale data pipelines for multimodal datasets and in deploying ML models to edge devices.

Required skills

• Kubernetes
• AWS, GCP or Azure cloud platforms
• MLflow, Weights & Biases, DVC
• GitHub Actions, GitLab CI
• Encord, Scale AI, Lightly
• CI/CD pipelines for ML workloads
• Model registry and artifact versioning
• Data versioning and large‑scale database architectures