MLOps Engineer: Reproducible ML Pipelines for Autonomy

Signal Processing Engineer (RF Processing & Analytics); Paris; On-site; EUR 90,000 - 150,000; Full time

Job summary

Harmattan AI is seeking an MLOps Engineer to own the training and evaluation pipelines for its autonomous defense models. You will standardize tooling, automate CI, and ensure reproducibility so modelers can focus on model development rather than infrastructure.

The role is based in Paris, Lausanne, or Zurich and emphasizes rigorous engineering, ownership, and high-impact technical challenges within a defense-focused tech leader.

Qualifications

• Educational background in a STEM field or equivalent practical experience.
• MLOps experience: built and maintained ML pipelines, CI, and experiment tracking in production or research settings.
• Strong Python and software engineering for infrastructure.
• Bonus: experience wiring pipelines to on-device or hardware-in-the-loop testing.
• Attributes: systematic, reliability-minded, service-oriented to reduce friction.
• Commitment to Harmattan AI's mission of defensive edge through ethical, high-impact technology.

Responsibilities

• Build and maintain reproducible training and evaluation pipelines and templates.
• Bring CI to ML work and ensure runs are comparable across code, config, and models.
• Maintain a model lifecycle registry from sandbox to production.
• Keep results traceable across the team with experiment tracking and logging.
• Wire on-device and hardware-in-the-loop test runs into automation and collect results.

Skills

Python

ML pipelines

CI/CD

Experiment tracking

Software engineering

Education

STEM degree

Tools

Model registry tooling

CI tooling

Job description

Harmattan AI is seeking an MLOps Engineer to own the training and evaluation pipelines for its autonomous defense models. You will standardize tooling, automate CI, and ensure reproducibility so modelers can focus on model development rather than infrastructure.

The role is based in Paris, Lausanne, or Zurich and emphasizes rigorous engineering, ownership, and high-impact technical challenges within a defense-focused tech leader.