AI Engineer – Model Training & Deployment

About the Opportunity

Become part of a dynamic, early-stage startup in the field of industrial robotics, located in Munich, as a junior AI Engineer. You will join a dedicated machine learning and robotics group to develop the deep learning systems that empower robotic work cells for demanding industrial processes such as welding, surface finishing, and coating. This is a hands-on position where your work will directly contribute to real-world deployments and allow you to take on responsibilities in model deployment and MLOps as the product evolves. As one of the first team members, you may be eligible for company equity.

Key Responsibilities

• Develop and optimize deep learning models that form the foundation of the robotics solutions.
• Continuously improve model architectures and training processes to enhance practical performance in industrial environments.
• Assist in deploying trained models to both customer sites and edge computing platforms.
• Work closely with the rest of the ML and robotics team to achieve core engineering objectives.
• Participate in installations and troubleshooting at customer locations and in edge environments.
• Conduct controlled experiments, report on critical metrics, and use results to inform improvements.

Required Skills and Experience

• At least 1 year of direct experience training deep learning models using Python and PyTorch (work can be academic, research, or professional).
• Ability to use Docker for replicating environments and deploying models.
• Proficient in Linux CLI (command-line interface) tasks.
• Practical experience deploying models to real or simulated production environments.

Preferred Qualifications

• Knowledge of cluster job management systems such as Slurm.
• Hands-on experience with tools like ONNX for model compatibility and deployment, or an interest in on-device/edge AI deployment.
• Exposure to or enthusiasm for computer vision, robotics, or manipulation of physical systems.
• Experience with data management/versioning tools such as DVC.
• Understanding of cloud-based deployment workflows.
• Fluency in English; German language skills are beneficial.
• Meticulous experimental approach and a data-driven decision making process.

Compensation, Benefits, and Additional Details

• Salary is competitive and proportionate to experience.
• Equity options available given early team membership.
• Opportunity to influence the architecture and roadmap of a next-generation robotics platform.

Additional Information

• This is a strictly on-site role in Munich, Bavaria, Germany.
• Applicants must be legally entitled to work in Germany, as visa sponsorship is not provided for this position.