talentyGo

AI Engineer – Model Training & Deployment

Clera

📍 Munich, DE0💼 Full-time🕐 today
Apply now →

Sign up free in 30 seconds: you also get the AI match score with your resume.

Role overview

Clera is hiring for the AI Engineer – Model Training & Deployment role in Munich, DE. It is full-time, Mid-level level, in the Tech sector. It was posted today.

On TalentyGo you can review this job and apply more effectively: Charlie prepares an ATS-optimized resume and a cover letter tailored to "AI Engineer – Model Training & Deployment" at Clera in about a minute. Before you apply, you can also check how well your profile fits, with a match score based on skills, experience, location and seniority.

Role
AI Engineer – Model Training & Deployment
Company
Clera
Location
Munich, DE
Work mode
On-site
Employment
Full-time
Seniority
Mid-level
Sector
Tech
Posted
today

Description

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.

Find more English Speaking Jobs in Germany on Arbeitnow

The market for this role in Munich

TalentyGo lists 5338 similar roles (1 in Munich), 23% remote. Charlie ranks them against your CV, each with a clear score.

Similar roles
5338
Remote
23%
New / 7d
142

Similar jobs

Research Engineer / Research Scientist / AI Systems Engineer, RSI
📍 San Francisco · Remote · tech
Member of Technical Staff (Software Engineer, GPU Cluster Infrastructu
📍 San Francisco · tech
Software Engineer, Vulnerability Management
📍 US - Remote · Remote · tech
Software Engineer, Platform Engineering (L2)
📍 Remote - US · Remote · tech
Software Engineer
📍 Remote - US · Remote · tech
Director of Engineering, AI Platform
📍 San Francisco · tech
See all similar jobs →
Apply now →

TalentyGo is an aggregator of job postings from public sources. Always verify information directly with the company. Applications go through the original company website; TalentyGo does not manage hiring processes.