Senior Software Engineer, Perception Architecture

About Stack:

Stack is developing revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency of modern operations. Stack's autonomous technology incorporates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies, empowering us to create innovative solutions that address the needs and challenges of the dynamic trucking transportation industry. With decades of experience creating and deploying real world systems for demanding environments, the Stack team is dedicated to developing an autonomous solution ecosystem tailored to the trucking industry's unique demands.

About the Role:

The Perception Architecture team is responsible for tackling complex, cross-cutting issues in Stack AV’s approach to perception development and accelerating our delivery of perception capabilities. Many problems in the self-driving trucking industry are not well represented in the literature, requiring novel approaches or formulations to tackle challenging perception problems for the product.

As a Senior Software Engineer, you will develop foundational ML architecture and systematic approaches to challenging, cross-cutting perception problems to ensure the self-driving system scales robustly and efficiently. This role will work closely with other teams to identify pain points and forward looking challenges, develop novel experiments to define future direction, and collaborate with other AI teams to convert these discoveries into products.

Responsibilities:

Contribute to the technical direction of the Perception Architecture team and the broader perception organization.

Design and develop core machine learning components and architectures that enable the perception system to scale and reliably address complex, long-tail driving scenarios.

Drive the initial implementation and prototyping of key architectural decisions, such as handling long tail challenges or long range detection.

Contribute to the improvement of model frameworks, architecture, and data pipelines to eliminate development bottlenecks and accelerate model iteration.

Lead challenging technical topics and build consensus across sister teams (e.g., Actor Detection, Scene Understanding, Tracking) and stakeholders to ensure autonomy-wide alignment.

Qualifications:

BS (with 4+ years of experience), MS (with 2+ years of experience), or PhD (with 1+ years of experience) in a perception-related field, such as Robotics, Computer Vision, or Machine Learning.

Extensive experience architecting, training, and evaluating deep learning models for challenging problem spaces.

Track record of driving applied research or engineering projects from conception and experimentation to successful productization.

Strong experience in software engineering, machine learning algorithm design, and building data/metrics pipelines for ML development.

Fluency in Python and hands-on experience with C++.

Experience delivering detection, segmentation, tracking, or other perception solutions for real-time robotic applications, with prior experience in sensor fusion being highly desirable.

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