Senior, ML Engineer - Tracking

Ladders; United States; Remote; USD 177,000 - 213,000; Full time

Benefits offered by this job

Premium medical/dental/vision

401K with 6% match

Flexible schedule & generous vacation

AD&D & Life Insurance

Job summary

Ladders is seeking a Senior ML Engineer - Tracking to enable autonomous vehicle perception, tracking, and sensor fusion. You will design, train, and deploy ML models for multi-object tracking, and build scalable data pipelines and production software in Python/C++.

You will collaborate with cross‑functional teams to validate performance, refine algorithms, and ensure safety. Remote work is available for US‑based candidates, with competitive compensation and comprehensive benefits.

Qualifications

• Requires a strong background in autonomous vehicle perception or robotics.
• Experience deploying ML models for perception, localization, or sensor fusion.
• Proficient in PyTorch and software engineering best practices.

Responsibilities

• Design, develop, and deploy ML models for multi-object tracking and sensor fusion.
• Build scalable training/evaluation workflows using PyTorch.
• Improve tracking algorithms for vehicle pose and kinematics.
• Analyze data to identify issues and drive improvements.
• Develop production-grade software in C++ and Python.
• Lead design reviews and mentor teammates.

Skills

ML model development

Software engineering

Leadership

Cross-functional collaboration

Education

Bachelor's degree in CS/EE/Robotics

Master's degree in related field

PhD in related field

Tools

PyTorch

Python

C++

Job description

For our client, we are seeking a Senior, ML Engineer - Tracking to join the team of a leader in the Manufacturing & Automotive space.

This role will focus on advancing machine learning solutions that help enable autonomous vehicle perception, tracking, and sensor fusion capabilities. You will work across model development, data pipelines, and production software to improve the quality, safety, and reliability of tracking systems. The position also partners closely with cross-functional engineering teams to validate performance, refine algorithms, and bring scalable solutions into production.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $177,300 – $212,800 annually

Responsibilities

• Design, develop, and deploy ML models for multi-object tracking and sensor fusion
• Create scalable training and evaluation workflows using PyTorch and large datasets
• Enhance tracking and sensor fusion algorithms for vehicle pose and kinematics
• Analyze vehicle data to identify performance issues and drive improvements
• Develop efficient production software in C++ and Python throughout the development lifecycle
• Define strategies for evaluation and validation to ensure tracking quality and safety
• Collaborate with cross-functional teams to integrate autonomous driving capabilities
• Provide technical leadership through design and code reviews, mentoring, and best practices

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Robotics, or a related field with 6+ years of experience, or a Master’s with 3+ years, or a PhD with 1+ year
• Experience with autonomous vehicle or robotics perception systems
• Strong background in developing and deploying ML models for perception, localization, or sensor fusion
• Proficiency in PyTorch and modern ML tools for training and optimization
• Solid understanding of 3D geometry and probabilistic estimation
• Experience with large multimodal datasets and scalable processing pipelines
• Strong software engineering skills in Python and C++, including algorithms and performance optimization

Benefits

• 100% paid medical, dental, and vision premiums for full-time employees
• 401K plan with a 6% employer match
• Flexible schedule and generous paid vacation available immediately
• AD+D and Life Insurance

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.