Machine Learning Engineer, ADAS
HybridHerzliya, Tel Aviv, Israel
Job Summary
Train, debug, and improve computer vision and 3D perception models while iterating based on clear evaluation signals across the full ML lifecycle. Build scalable data pipelines including auto-labelling and pseudo-labelling to accelerate development, and contribute to offline pipelines for tracking and 3D reconstruction. Deliver core ADAS perception capabilities for detection, classification, and instance segmentation focused on lanes, objects, traffic signs, and traffic lights. Own work end-to-end, deciding next priorities based on system performance gaps and balancing online latency-constrained models with offline scale improvements.
Required Qualifications
- CV-focused deep learning systems
- applied ML engineering
- 3D perception concepts or pipelines
- LiDAR
- multi-view geometry
- tracking
- 3D reconstruction
- owning work end-to-end
- evaluation
- dataset generation
- pragmatic problem-solving
- working under real product constraints
- improve real-world driving performance through better perception
- hybrid working model
- in-person collaboration in dedicated office spaces
- focused time working remotely
- core hours
- hands on in vehicle workshops and labs
- learning and development budgets
- training
- conferences
- growth
- health insurance
- dental
- enhanced maternity and paternity leave
- retirement or pension
- access to therapists
- wellbeing partnerships
- team socials
- location dependant salaries
- meaningful equity
- relocation support
- visa sponsorship where applicable
Desired Qualifications
- passionate about autonomy
- keen to learn
- not ticking every box
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