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Harmattan AI

ML Ops Engineer

Paris
Level
Mid
Work type
On-site · Paris

Not stated in the posting: salary, visa.

Open. First seen 2 October 2026.

Apply on the company's site →

About the role

About Us

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.

Harmattan AI's standard text

Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.

ABOUT THE ROLE

Our ML teams build and optimize the models at the core of our autonomy stack. As a team scales, the workflow the models run on needs to move from a manual, organically grown setup onto a controlled, automated, and reproducible footing.

As an MLOps Engineer, operating out of Paris, Lausanne, or Zurich, you will own that machinery, across training and evaluation pipelines, CI, experiment tracking, and reproducibility, so that models are trained, benchmarked, and compared in a controlled and repeatable way. You free the modelers to focus on models rather than infrastructure, and you set the standard the team builds on.

RESPONSIBILITIES

  • Training & Evaluation Pipelines: Build and maintain the reproducible training and evaluation pipelines the modelers run on, along with the pipeline templates and tooling they build on. The verdict on model quality stays with the modelers.
  • CI & Reproducibility: Bring CI to ML work and make runs genuinely comparable across code, config, and models.
  • Model Registry: Maintain a model lifecycle registry, from sandbox to production.
  • Experiment Tracking & Logging: Keep results comparable and traceable across the team.
  • Test Automation: Help wire on-device and hardware-in-the-loop test runs into automation and collect the results.

CANDIDATE REQUIREMENTS

  • Educational Background: A degree in a STEM field, or equivalent practical experience. Practical pipeline, CI, and reproducibility experience matters more than the specific degree.
  • MLOps Experience: Built and maintained ML pipelines, CI, and experiment tracking in a real production or research setting, ideally taking a manual flow and making it controlled and reproducible.
  • Engineering: Strong in Python and software engineering for infrastructure.
  • Bonus: Experience wiring pipelines to on-device or hardware-in-the-loop testing.
  • Attributes: Systematic, reliability-minded, and service-oriented so the team is enabled, pragmatic, and good at reducing friction.
  • Commitment: 100% dedication to Harmattan AI's mission of providing a defensive edge to allied nations through ethical, high-impact technology.
Harmattan AI's standard text

We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

What this role asks for

Particular to this role

MLOps · Test Automation

Rare in Harmattan AI's other 116 open postings.

Standard for data science / ML roles

Machine Learning · Python

Common in data science / ML postings at any company.

85% of this description is written for the role. The rest is Harmattan AI's standard text, folded away below.

Read against Harmattan AI's other open postings on this site.

The team: R&D HIRES STEADILY

This role is one of 96 open in R&D. 37 were posted in the last 30 days and the oldest in January: a team that hires all year rather than one being built.

WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS

Python (39 of 96), C++ (38 of 96), Embedded Systems (37 of 96), C (17 of 96), Computer Vision (16 of 96), Linux (15 of 96), Machine Learning (14 of 96)

OTHER ROLES ON THIS TEAM

From the team and dates on Harmattan AI's own job board.

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