Job Description

Want to be part of transforming road freight – for good? Einride is showing the world a new way to move, based on the latest digital, electric and autonomous technologies. Through freight capacity as a service, we enable businesses around the world to accelerate towards their sustainability goals.

Founded in 2016, Einride became the first company in the world to deploy a cab-less autonomous electric vehicle on a public road (Sweden, 2019). In 2022, we were the first to successfully operate such a vehicle on a US public road. Today our award-winning technology has been launched across 8 countries (and counting). Our clients are some of the world’s biggest shippers, including Fortune 500 companies. We are also operating Sweden’s largest truck dedicated public charging network and counting.

Your mission when joining as a Senior 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 also be responsible for the coordination of the data collection and for driving the implementation of automated data mining techniques to identify the most valuable data sequences to train our models on.

You will:

• Data mining: Implement automated data mining techniques to identify the best data sequences for model training
• Build & Automate ML Pipelines: Design, implement, and maintain robust, automated CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines for the entire machine learning lifecycle, from data ingestion to model deployment in the vehicle.
• Manage Large-Scale Datasets: Develop and manage scalable data pipelines for processing and versioning petabytes of AV sensor data, including LiDAR, camera, and radar feeds. Ensure data quality and traceability for model training and validation.
• Model Deployment & Optimization: Deploy ML models (e.g., perception, prediction, planning) onto embedded, resource-constrained automotive hardware. Profile and optimize models for latency, throughput, and power efficiency using techniques like quantization and pruning.
• Infrastructure Management: Build and manage scalable training and inference infrastructure on cloud platforms (e.g., GCP, AWS, Azure) and on-premise clusters using tools like Kubernetes and Docker.
• Monitoring & Validation: Implement comprehensive monitoring solutions to track model performance, data drift, and system health both in simulation and in real-world fleet operations. Develop validation strategies to ensure model safety and reliability.
• Collaboration & Tooling: 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 have:

• 7+ years of professional experience in an MLOps, DevOps, or Software Engineering role with a focus on machine learning 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).

This is a full-time position based in Gothenburg or Stockholm. You will be part of a truly diverse, high performing team with a common passion for sustainability and making things happen in an innovative way. We recommend that you submit your application as soon as possible since selection and interviews are held continually.

At Einride, we are innovators, building solutions the world has never seen before – but urgently needs. That’s why we take action, and it’s why we are always eager to be challenged. We know that our best innovations come from having a diverse mix of people, including those of different experiences, career paths, and walks of life. By coming together and sharing our perspectives openly – by disagreeing, discussing, and committing – we deliver greater impact.

Please note that as part of our standard recruitment process, we conduct a background control on the final candidate for this role. This may include verification of education, employment history, any relevant professional certifications or other information that may be of our interest.