Machine Learning Staff Engineer – ADAS Online

About the Role

Join our high-performance ADAS Online team dedicated to pushing the boundaries of machine learning and AI for advanced scene understanding and environmental perception. As a Machine Learning Staff Engineer, you will lead the development of cutting-edge in-vehicle spatial awareness algorithms, maintaining hands-on involvement in model design, experimentation, and optimization. You will serve as a senior technical leader and mentor within a dynamic, fast-paced team.

This role focuses on creating a spatial awareness system using modern transformer and end-to-end architectures to convert vehicle sensor inputs combined with real-time 3D cloud map data into semantically rich 3D environments, detecting static and dynamic objects.

Key Responsibilities

• Set and guide the technical vision for physical AI algorithms.
• Formulate and implement a technical roadmap targeting state-of-the-art reinforcement learning with physical AI world models.
• Design, build, and enhance ML and vision transformer models for 3D environment understanding and planning, including techniques like Gaussian Splatting, Diffusion, object detection, multi-object tracking, semantic segmentation, and occupancy modeling.
• Create multi-modal sensor fusion methods integrating camera, LiDAR, and RADAR data to construct accurate 3D environments.
• Evaluate and incorporate larger end-to-end models where appropriate.
• Employ advanced machine learning methodologies such as Transformers, representation learning, and large-scale model training to boost perception accuracy.
• Lead structured experimental design and benchmarking to achieve quantifiable improvements in system robustness and precision.
• Convert research innovations into dependable, scalable machine learning solutions.
• Mentor and provide technical leadership to perception engineers within the team.

Required Qualifications

• Minimum of 7 years’ experience in machine learning, vision transformers, diffusion models, or computer vision.
• Deep understanding of modern deep learning architectures.
• Extensive practical experience using PyTorch or similar frameworks.
• Demonstrated success in developing and iterating on large-scale ML models.
• Strong mathematical expertise in optimization and probabilistic modeling.
• Proven ability to deliver measurable performance improvements in ML systems.
• Experience providing technical direction within small engineering teams.

Preferred Qualifications

• Background in autonomous systems or robotics perception.
• Authorship of patents or publications in machine learning or perception fields.
• Familiarity with 3D data formats such as Gaussian Splatting, point clouds, BEVs, voxel grids, and 3D tools like Unity.
• Experience with large-scale training or foundational AI models.
• Track record of mentoring engineers in advanced machine learning topics.

What We Provide

• A competitive pay package.
• Resources and time for personal growth and continued education, including a development budget and paid learning days.
• Paid access to e-learning platforms like O’Reilly.
• Enhanced parental leave and paid time off to care for loved ones or volunteer.
• Flexible working arrangements combining office and remote days (typically two days in office, three days flexible).
• Home office setup budget and monthly allowances.
• Opportunities to work remotely from your home country or abroad for designated periods annually.
• Generous holiday policies with an extra day off for your birthday.
• Annual team events such as Hackathon and DevDays for innovation and collaboration.
• An inclusive global culture with colleagues from over 80 nationalities.
• Additional local perks tailored to your location.

Team Overview

You will be part of the ADAS & ADS Product Unit, focusing on creation and real-time updating of HD maps that support leading automotive manufacturers and technology companies worldwide. The team includes applied scientists, engineers, and data experts collaborating on innovative location-based technologies.

Equal Opportunity

We value diversity and encourage applicants from all backgrounds to apply, including those from underrepresented communities. We use AI tools in our hiring process to aid our recruitment team, but all final decisions are made by humans.