Staff ML Engineer, Dynamic World Perception

StackAV · Pittsburgh

Data & AIRemoteposted 9mo ago

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 Dynamic World Perception team is responsible for real-time detection of road actors and properties. This includes developing occupancy networks and other perception algorithms to accurately identify and classify all dynamic elements within the driving environment. We're looking for a Staff or Senior Engineer to lead the development, maintenance, and enhancement of our long-range detection capabilities, ensuring the required safety and performance standards are met or exceeded.

Responsibilities:

Lead initiatives in the team to deliver state-of-the-art closed-and open-world detection capabilities.
Contribute to expansion and fusion of existing detection models to support improving performance and extending performance at range.
Contribute to improvement of model frameworks, architecture, and data pipelines.
Develop robust software for onboard vehicle deployment, optimizing for real-time, resource-constrained, and safety-critical environments.
Drive highly cross-functional features and workstreams from problem statement to delivery.
Contribute to the technical direction of the team and broader perception org.
Align stakeholders with strong presentation and communication skills.
Lead challenging technical topics and build consensus.

Qualifications:

Extensive experience architecting, training, and deploying deep learning models 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 delivering detection, segmentation, and/or tracking solutions for real-time robotic applications. Prior experience in sensor fusion is highly desirable.
Strong experience in software engineering and machine learning algorithm design.
Fluency in Python.
Experience with C++.

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