Senior ML Engineer – Perception for L4 Autonomy (Remote)

Stack AV; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Stack AV is seeking a Senior Machine Learning Engineer to advance online/offline perception systems for L4 autonomous driving. You will develop, maintain, and optimize algorithms that integrate LiDAR, cameras, GPS, and maps to ensure robust, real-time performance in safety-critical environments.

The role emphasizes deep learning deployment, sensor fusion, and software engineering in a fast-moving, autonomous trucking context, with a flexible remote work option within the United States.

Qualifications

• Experience architecting, training, and deploying deep learning models (transformers or diffusion or flow) into real-world environments.
• Track record of driving applied research projects from start to completion, including conception, problem definition, experimentation, iteration, and finally publication or productization.
• Experience in software engineering and machine learning algorithm design.
• Prior experience in sensor fusion and/or online mapping is highly desirable.
• Fluency in Python.
• Experience with C++.

Responsibilities

• Work in the team to deliver state-of-the-art online and offline perception and generative AI algorithms and systems for L4 self-driving vehicles.
• Write robust software for real-time, resource-constrained, safety-critical applications.
• Drive features and work streams from problem statement to delivery.
• Proactively identify limitations with the existing online mapping system and drive improvements.
• Align internal stakeholders with strong presentation and communication skills.
• Build consensus and execute on team priorities.

Skills

Python

C++

Deep learning

Sensor fusion

Job description

Stack AV is seeking a Senior Machine Learning Engineer to advance online/offline perception systems for L4 autonomous driving. You will develop, maintain, and optimize algorithms that integrate LiDAR, cameras, GPS, and maps to ensure robust, real-time performance in safety-critical environments.

The role emphasizes deep learning deployment, sensor fusion, and software engineering in a fast-moving, autonomous trucking context, with a flexible remote work option within the United States.