Medium
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior, ML Engineer - Road & Lane Detection in New York.
In this role, you will be at the forefront of autonomous vehicle perception, developing machine learning models that interpret and predict road and lane structures in complex environments. You will work with multi-modal sensor data, including cameras, LiDAR, and radar, to create robust 3D representations of driving surfaces. Your contributions will directly influence vehicle navigation and safety, optimizing algorithms for real‑world deployment. You will collaborate across software, robotics, and hardware teams, guiding junior engineers and integrating cutting‑edge research into production‑grade ML pipelines. This role is ideal for someone passionate about AI, computer vision, and autonomous driving, seeking a fast‑paced environment with tangible impact on the future of mobility.
Accountabilities:
Develop and optimize computer vision algorithms for road and lane detection in monocular and multi‑modal contexts
Design and implement deep learning models for BEV (bird’s eye view) representations integrated into planning and control pipelines
Analyze model performance, data distributions, and edge cases using advanced data science techniques
Build efficient pipelines for large‑scale data processing, annotation, augmentation, and domain adaptation
Deploy and optimize ML models for real‑time inference on automotive‑grade hardware
Collaborate cross‑functionally with robotics, software, hardware, product, and operations teams to ensure seamless system integration
Mentor junior engineers and contribute to the technical roadmap, staying current with the latest advancements in ML and computer vision
Requirements:
Bachelor’s degree with 6+ years or Master’s degree with 3+ years of professional experience in Machine Learning Engineering, Autonomous Vehicles, Robotics, or a related field
Strong expertise in 3D BEV space modeling, lane and road geometry, multi‑camera calibration, and sensor projection
Proficiency in Python and PyTorch, with experience translating research code into production‑ready systems
Hands‑on experience with multi‑modal sensor data (camera, LiDAR, radar) and data management pipelines
Experience deploying and optimizing ML models for embedded and real‑time systems
Strong analytical, problem‑solving, and communication skills, with a track record of mentoring or leading technical teams
Preferred: PhD in ML or Data Science, CUDA programming, custom PyTorch operations, publications in top‑tier ML/Computer Vision conferences, experience with distributed training and multi‑GPU systems
Benefits:
Competitive salary ($199,200–$298,800) plus bonus and stock options
100% paid medical, dental, and vision coverage
401(k) plan with 6% employer match
Flexible schedule and generous paid vacation, plus company‑wide holiday closures
Life and AD&D insurance
Collaborative, energetic, and team‑focused work environment
Opportunities for professional growth and mentorship in cutting‑edge ML and autonomous vehicle technologies
Hybrid or remote work options available in the United States
Why Apply Through Jobgether? We use an AI‑powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role’s core requirements. Our system identifies the top‑fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
#J-18808-Ljbffr
In this role, you will be at the forefront of autonomous vehicle perception, developing machine learning models that interpret and predict road and lane structures in complex environments. You will work with multi-modal sensor data, including cameras, LiDAR, and radar, to create robust 3D representations of driving surfaces. Your contributions will directly influence vehicle navigation and safety, optimizing algorithms for real‑world deployment. You will collaborate across software, robotics, and hardware teams, guiding junior engineers and integrating cutting‑edge research into production‑grade ML pipelines. This role is ideal for someone passionate about AI, computer vision, and autonomous driving, seeking a fast‑paced environment with tangible impact on the future of mobility.
Accountabilities:
Develop and optimize computer vision algorithms for road and lane detection in monocular and multi‑modal contexts
Design and implement deep learning models for BEV (bird’s eye view) representations integrated into planning and control pipelines
Analyze model performance, data distributions, and edge cases using advanced data science techniques
Build efficient pipelines for large‑scale data processing, annotation, augmentation, and domain adaptation
Deploy and optimize ML models for real‑time inference on automotive‑grade hardware
Collaborate cross‑functionally with robotics, software, hardware, product, and operations teams to ensure seamless system integration
Mentor junior engineers and contribute to the technical roadmap, staying current with the latest advancements in ML and computer vision
Requirements:
Bachelor’s degree with 6+ years or Master’s degree with 3+ years of professional experience in Machine Learning Engineering, Autonomous Vehicles, Robotics, or a related field
Strong expertise in 3D BEV space modeling, lane and road geometry, multi‑camera calibration, and sensor projection
Proficiency in Python and PyTorch, with experience translating research code into production‑ready systems
Hands‑on experience with multi‑modal sensor data (camera, LiDAR, radar) and data management pipelines
Experience deploying and optimizing ML models for embedded and real‑time systems
Strong analytical, problem‑solving, and communication skills, with a track record of mentoring or leading technical teams
Preferred: PhD in ML or Data Science, CUDA programming, custom PyTorch operations, publications in top‑tier ML/Computer Vision conferences, experience with distributed training and multi‑GPU systems
Benefits:
Competitive salary ($199,200–$298,800) plus bonus and stock options
100% paid medical, dental, and vision coverage
401(k) plan with 6% employer match
Flexible schedule and generous paid vacation, plus company‑wide holiday closures
Life and AD&D insurance
Collaborative, energetic, and team‑focused work environment
Opportunities for professional growth and mentorship in cutting‑edge ML and autonomous vehicle technologies
Hybrid or remote work options available in the United States
Why Apply Through Jobgether? We use an AI‑powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role’s core requirements. Our system identifies the top‑fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
#J-18808-Ljbffr