MLOps Engineer

MLOps Engineer

Einride

Gothenburg or Stockholm, Sweden

Your mission when joining as an MLOps Engineer at Einride will be to build and maintain the infrastructure that enables the development, deployment, and monitoring of ML/DL models for our self-driving technology.

You will:

• Implement and maintain robust CI/CD/CT pipelines for the entire ML lifecycle
• Develop and manage pipelines for processing and versioning petabytes of AV sensor data, ensuring data quality and traceability for model training and validation
• Deploy ML/DL models onto embedded, resource-constrained automotive hardware
• Build and manage scalable training and inference infrastructure on cloud platforms and on-premise clusters
• Implement solutions to track model performance, data drift, and system health both in simulation and in real-world fleet operations
• Work closely with ML researchers, robotics engineers, and software developers to understand their needs and provide the necessary tools and platforms to accelerate the ML development cycle

We expect you to:

• 5+ years of professional experience in an MLOps, DevOps, or Software Engineering role with a focus on ML systems
• Strong programming skills in Python and proficiency with common ML frameworks (e.g., TensorFlow, PyTorch)
• Hands-on experience with MLOps tools and platforms such as Kubeflow, MLflow, or Weights & Biases
• Proven experience with containerization and orchestration technologies (Docker, Kubernetes)
• Solid experience with at least one major cloud provider
• Experience building and maintaining CI/CD pipelines using tools like Jenkins/GitLab CI/CircleCI

Nice to have:

• Experience in the autonomous driving industry
• Experience deploying models to embedded systems or edge devices (e.g., NVIDIA Jetson, DRIVE platforms)
• Knowledge of automotive software development processes and safety standards
• Experience with simulation platforms for AVs (e.g., CARLA, NVIDIA DRIVE Sim)