ML Ops Engineer

Posted 16 Days Ago
Be an Early Applicant
3 Locations
In-Office
Mid level
Artificial Intelligence • Computer Vision • Machine Learning • Robotics • Defense • Manufacturing
Building the Future of Autonomous Warfare. With Speed and Intelligence.
The Role
Build, maintain, and automate reproducible training and evaluation pipelines, CI, experiment tracking, and a model registry. Integrate test automation including on-device and hardware-in-the-loop runs, ensure reproducibility and traceability, and enable modelers to focus on model quality.
Summary Generated by Built In
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.

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.

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

Skills Required

  • Degree in a STEM field or equivalent practical experience
  • Built and maintained ML pipelines, CI, and experiment tracking in production or research settings
  • Strong Python skills and software engineering for infrastructure
  • Experience wiring pipelines to on-device or hardware-in-the-loop testing
  • Systematic, reliability-minded, service-oriented attributes
  • Commitment to company mission and ethical defense work

Harmattan AI Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Harmattan AI and has not been reviewed or approved by Harmattan AI.

  • Fair & Transparent Compensation Pay ranges are publicly shown for multiple U.S. roles (e.g., $140k–$200k base) and appear broadly in line with late‑stage startup/defense‑tech expectations based on the postings cited.
  • Equity Value & Accessibility Equity is repeatedly referenced in several job postings as part of total compensation, which can increase upside potential at a recently funded, high‑valuation company.
  • Strong & Reliable Incentives Sign‑on bonuses are explicitly mentioned in a hiring post for candidates who can start quickly, indicating the use of cash incentives in at least some hiring situations.

Harmattan AI Insights

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The Company
HQ: Paris, Île-de-France
131 Employees

What We Do

Harmattan AI is rising as a next-generation defense prime, building the future of autonomous warfare. We leverage AI-driven autonomy, real-time intelligence, and conflict-ready production to deliver attritable systems and autonomous mission management software. Designed for the real-world needs of warfighters, our solutions enable faster deployment, sharper decision-making, and battlefield dominance.

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