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Harmattan AI

Computer Vision Engineer - Tracker

Lausanne
Salary
Not stated
Level
Mid
Work type
On-site · Lausanne
Visa
Not stated

Open. First seen 16 October 2026.

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.

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.

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

As a Computer Vision Engineer in the Computer Vision Tracker team, you will join us at a very early stage, giving you a unique opportunity to heavily influence the technical direction of the team. Operating out of Lausanne, Paris, or Zurich, you will focus on creating a global 3D Object Tracking pipeline, at the intersection between the Computer Vision, Sensor Fusion and GNC teams.

Responsibilities

  • Computer Vision Algorithm Development: Research and implement state-of-the-art Computer Vision approaches to Object Tracking in multiple modalities and scenarios, combining classical and geometrical methods with AI detection models developed in-house.
  • Multi-Sensor Fusion: Fuse data from multiple sensors (Cameras, IMU, Radar, etc.) to provide high-precision target estimation and robust tracking through challenging conditions.
  • Edge Optimization for Low-Compute Deployment: Optimize and embed tracking algorithms on heterogeneous platforms with limited compute resources, ensuring real-time performance alongside other software bricks running on the drone.
  • Cross-Team Collaboration: Work closely with the GNC, Sensor Fusion, and AI teams to integrate your tracking pipelines into a seamless, production-ready environment.
  • Research & Innovation: Stay at the absolute forefront of scientific trends in computer vision, tracking algorithms, and sensor fusion to introduce cutting-edge methodologies to the product.
  • Mentorship: Depending on seniority, support the team by managing or mentoring junior engineers.

Candidate Requirements

  • Educational Background: A strong academic record with a degree in a STEM field (e.g., Computer Science, Robotics, Engineering, Mathematics).
  • Embedded Algorithmic Expertise: Proven track record in the research, development, and productization of Computer Vision & Sensor-Fusion algorithms in hardware-constrained environments.
  • Technical Competence: Strong proficiency in C++ and Python for real-time systems. Experience with optimizing code for edge deployment.

Nice to have

  • Highly structured, analytical, task-aligned, and research-oriented.
  • Excellent communication and influence skills, with the ability to effectively translate and present complex algorithmic trade-offs to downstream users and senior stakeholders.
  • Thrives under pressure in a fast-paced environment with a “no-task-is-too-small” mentality toward building foundational team infrastructure.
  • Commitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence.

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

Other openings for this role

2 postings for this role in Lausanne since 5 October 2026, 1 still open. None has been taken down and posted again.

  • 16 October 2026 – open (this posting)
  • 5 October 2026 – closed 16 October 2026

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