AI Engineer – Model Training & Deployment

Meyandy LLC

München

Vor Ort

EUR 45.000 - 70.000

Vollzeit

14 Tage+
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Benefits dieser Stelle

Equity for early team members

Zusammenfassung

Meyandy LLC in Munich is seeking a junior AI Engineer to join a focused ML and robotics team. You will work on the core deep learning stack enabling 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. Equity for early team members is available.

Qualifikationen

  • 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.

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
Deep learning
Linux CLI

Tools

Docker
Slurm
ONNX
DVC

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.


Eligibility

Candidates must be eligible to work in Germany; visa sponsorship is not provided.


Mots-clés : Engineering.

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