JobCubby JobCubby
Sign up
Harmattan AI

Machine Learning Research Engineer – Visual Navigation

Harmattan AI Paris, Ile-de-France, France

Defense and Space Manufacturing · 201-500 employees

Oct 19
machine-learning Senior (5-10 yrs) Full-time Switzerland
Create a free account to apply — email only, no card. You can also save this posting or score it against your profile with AI.

Applying here? Try the free cover letter tool — paste this posting and your résumé, no account needed.

About the role

Develop and optimize deep learning models that help drones interpret their environment and localize themselves, including deploying models on resource-constrained onboard platforms. Collaborate with navigation and embedded teams, manage reproducible training and evaluation pipelines, track research advances, and validate models through real-world flight testing.

What they look for

Deep Learning Computer Vision Python PyTorch PyTorch Lightning Machine Learning Edge AI Optimization Model Deployment MLOps Training and Evaluation Pipelines Data Curation Model Architecture Design Real-Time Localization Drone Navigation Visual-Inertial Odometry Field Testing

Requirements

Candidates should have a strong academic record in a STEM field and a proven record of researching and productizing deep learning computer vision models, ideally in drones, robotics, or autonomous vehicles. They should be proficient in Python and PyTorch or Lightning, have experience with MLOps and edge deployment optimization, and bring strong analytical, communication, and hands-on problem-solving skills.

Full description

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.

As an ML Research Engineer in the Visual Navigation team, you will join us at an early stage to heavily influence our technical direction. Operating out of Paris, Lausanne or Zurich, you will focus on developing Machine Learning models to enable our drones to navigate on the battlefield, with responsibilities ranging from data curation and model architecture definition to onboard inference on our drones.

Responsibilities

  • DL Algorithm Development: Design deep learning models to analyze a drone's environment in multiple modalities and enable its localization through time and space.
  • Edge AI Optimization: Embed models on heterogeneous platforms with limited shared compute. Optimize trade-offs between model speed and accuracy to minimize pipeline latency.
  • Cross-Team Collaboration: Partner with the VIO, Navigation, and Embedded Software teams to build a robust, real-time localization pipeline, communicating trade-offs clearly to stakeholders.
  • Research & Innovation: Stay at the absolute forefront of scientific trends in Deep Learning to introduce cutting-edge methodologies to the team.
  • Pipeline Management & MLOps: Build, heavily modify, and manage training, evaluation, and MLOps pipelines while ensuring reproducibility, robust logging, and version control.
  • Validation & Field Testing: Actively participate in real-world flight tests. Analyze in-field failures to continuously iterate and improve deployed models.

Candidate Requirements

  • Educational Background: Strong academic record with a STEM degree (e.g., Computer Science, Machine Learning, Robotics, Mathematics).
  • Deep Learning & Computer Vision Expertise: Proven track record of researching and productizing Deep Learning models for Computer Vision in the industry (Drones, Robotics, Autonomous Vehicles, etc.)
  • Technical Competence: Proficiency in Python and DL frameworks (PyTorch/Lightning). Experience with MLOps and edge deployment optimization.

Professional Attributes:

  • Highly structured, analytical, and research-oriented.
  • Excellent communicator able to translate complex algorithmic benchmarking to downstream users and stakeholders.
  • Thrives in a fast-paced environment with a hands-on, “no-task-is-too-small” mentality.
  • Commitment: 100% dedication to Harmattan AI’s mission, vision, and growth plans, ready to go the extra mile for operational excellence.

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

Similar roles