Machine Learning Research Engineer – Visual Navigation

Harmattan AI; Lausanne; In loco; CHF 130.000 - 185.000; Tempo pieno

Descrizione del lavoro

Harmattan AI, a next-generation defense company, is seeking an ML Research Engineer for the Visual Navigation team. You will work from Lausanne, Paris, or Zurich to develop ML models enabling drones to navigate autonomous battlefields, including data curation, model design, and onboard inference.

You will advance DL research and productize CV models for drone systems, collaborating with VIO, Navigation, and Embedded Software teams to push real-time localization pipelines.

Competenze

• Strong academic record in CS, ML, robotics, or math.
• Proven DL/CV research and productization experience in drones/robotics.
• Experience with Python and DL frameworks (PyTorch/Lightning) and edge deployment.

Mansioni

• DL Algorithm Development: design deep learning models for drone environment analysis and localization.
• Edge AI Optimization: embed models on heterogeneous platforms with constrained compute and minimize latency.
• Cross-Team Collaboration: partner with VIO, Navigation, and Embedded Software teams for a real-time localization pipeline.
• Research & Innovation: stay at the forefront of DL to introduce new methodologies.
• Pipeline Management & MLOps: build and manage training, evaluation, and MLOps pipelines with reproducibility and versioning.
• Validation & Field Testing: participate in real-world flight tests and iterate on deployed models.

Conoscenze

Python

PyTorch/Lightning

DL/Computer Vision

MLOps & edge deployment

Formazione

STEM degree

Descrizione del lavoro

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.