AI Engineer – Model Training & Deployment

United States Digital Space LLC; München; Vor Ort; EUR 50.000 - 70.000; Vollzeit

Benefits dieser Stelle

Equity participation

Zusammenfassung

United States Digital Space LLC in Munich is looking for a junior AI Engineer to join an early-stage robotics startup. You’ll work on the core ML and robotics stack, training and deploying models for real industrial environments, with room to grow into deployment and MLOps as the platform matures.

Equity is available for early team members, and the role is fully on-site in Munich with no visa sponsorship. You will train models, optimize architectures, support edge deployments, and collaborate on

Qualifikationen

• 1+ years hands-on experience training deep learning models using Python and PyTorch.
• Proficiency with Docker for environment replication and model deployment.
• Comfort working in a Linux / command-line environment.
• Experience deploying trained models to production or customer environments.

Aufgaben

• Train and implement deep learning models as part of the core robotics product.
• Iterate on model architectures and training pipelines to improve real-world performance.
• Support deployment of trained models to customer and edge environments.
• Collaborate closely with the ML and robotics team on the core technical roadmap.
• Contribute to on-site customer deployments and edge environment bring-up.
• Design and run reproducible experiments, tracking evaluation metrics to drive continuous improvement.

Kenntnisse

Python

PyTorch

Linux / CLI

Model deployment

Tools

Docker

Slurm

DVC

ONNX

Jobbeschreibung

About the Role

Join an early-stage industrial robotics startup in Munich as a junior AI Engineer on a focused ML and robotics team. You'll work on the core deep learning stack that enables robotic work cells to perceive and act in real industrial environments — covering tasks such as surface finishing, welding, and coating. This is a hands-on, high-impact role from day one, with room to grow into deployment and MLOps responsibilities as the platform matures. Early team members participate in equity.

Note: This role is fully on-site in Munich, Germany. Visa sponsorship is not available.

What You'll Do

• Train and implement deep learning models as part of the core robotics product.
• Iterate on model architectures and training pipelines to improve real-world performance.
• Support deployment of trained models to customer and edge environments.
• Collaborate closely with the ML and robotics team on the core technical roadmap.
• Contribute to on-site customer deployments and edge environment bring-up.
• Design and run reproducible experiments, tracking evaluation metrics to drive continuous improvement.

What We're Looking For

Must-haves:

• 1+ years of hands-on experience training deep learning models using Python and PyTorch (academic thesis, research project, or industry work counts).
• Proficiency with Docker for environment replication and model deployment.
• Comfort working in a Linux / command-line environment.
• Experience deploying trained models to production or customer environments.

Strong advantages:

• Familiarity with Slurm or other cluster job scheduling systems.
• Experience with ONNX or other model export / interoperability tools; interest in edge or on-device deployment.
• Background or strong interest in computer vision, robotics, or physical systems.
• Experience with data versioning tools such as DVC.
• Cloud deployment experience.
• Fluency in English; German is a plus.
• Rigorous, analytical mindset with a habit of structured experimentation.

Compensation & Benefits

Competitive salary commensurate with experience.

• Equity participation as an early team member.
• Opportunity to shape the technical direction of a growing robotics platform.

Location

This position is on-site in Munich, Bavaria, Germany. Candidates must be eligible to work in Germany; visa sponsorship is not provided.