Machine Learning Applied Scientist - ADAS Online

What You’ll Do

Develop a solid understanding of the team's physical AI roadmap and contribute ideas that improve algorithms within your area of ownership;
Implement and improve ML / vision transformer models for 3D awareness;
Produce instance detections and segmentation masks, instance tracking, and occupancy modelling;
Contribute to multi-modal fusion pipelines (camera, LiDAR, RADAR), building and validating components against defined requirements;
Apply Transformer-based and representation learning techniques within established frameworks, building confidence in large-scale model development;
Run experiments and benchmarks with guidance, producing clear results and contributing to the team's evaluation practices;
Participate in translating research into production, learning what makes ML solutions reliable and scalable;
Actively seek feedback from senior engineers and apply it to continuously improve the quality of your work.

What You'll Need

3+ years of experience in machine learning, vision transformers, diffusion, or computer vision;
Expertise in modern deep learning architectures;
Hands-on experience with PyTorch (or equivalent frameworks);
Understanding of what is needed to build and deploy large-scale ML models;
Strong ownership and bias toward execution;
Data-driven mindset with rigorous evaluation practices;
Ability to operate effectively in fast-paced environments;
Clear communication of technical trade-offs;
High standards for code quality and reproducibility;
Comfortable navigating ambiguity in complex technical domains.

Nice to Have

Experience in autonomous systems or robotics perception;
Publications or patents in machine learning or perception;
Experience with 3D data representations (meshes, point clouds, BEV, voxel grids).