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Open nowPosted 4 days ago

Data & ML Ops Lead

gravisrobotics10 open roles

Where
Zurich
Work mode
Hybrid
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Your applicationOpen nowData & ML Ops Leadgravisrobotics · Zurich

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This job: posted 4 days ago

The posting

Gravis Robotics is a high-growth Series A start-up backed by SoftBank, bringing Physical AI to the construction industry, turning heavy construction machines into autonomous robots.

Gravis began as an ETH Zurich spin-out, and our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of earthmoving machines in a gamified environment.

Backed by deep robotics research and now deployed across multiple countries with leading construction and equipment partners, our team is rapidly growing to bring this technology to a trillion-dollar industry.

The Gravis RACK is a machine-agnostic retrofit kit that adds autonomy to excavators and wheel loaders from 10 to 100+ tonnes: LiDAR and camera sensing, GNSS RTK, networking hardware and rugged edge compute that works offline. Paired with the Slate tablet and our Copilot software, it lets an operator run a machine manually, with AI assistance, or fully autonomously. Increasingly, we also build custom hardware to adapt our machines for highly specialized, robust applications beyond traditional excavation.

About the role

What you will do

  • 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

What we're looking for

  • 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

Bonus Qualifications

  • Experience working with robotics data (point clouds, camera streams, timeseries data).
  • Experience with Robotics & DevOps related tooling (Foxglove, Prometheus, Grafana)
  • Experience with databases
  • Demonstrated expertise with large-scale database architectures, indexing frameworks, and high-performance data retrieval

This is an opportunity to join a dynamic, multidisciplinary team and to be part of a company that is reshaping heavy construction.

Gravis is an equal opportunity employer. We are committed to building an inclusive and diverse team, and do not discriminate based on race, colour, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics.

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