Staff ML Engineer, Static World Perception

As a Staff ML Engineer at Stack, your primary responsibilities will involve developing and enhancing algorithms and systems for online map standards crucial for L4 self-driving vehicles. You will work closely with cross-functional teams to deliver state-of-the-art online and offline mapping solutions while proactively identifying and driving improvements to existing systems.

To qualify for the Staff ML Engineer role at Stack, candidates should have extensive experience in architecting, training, and deploying deep learning models. Additionally, a solid background in software engineering, experience with mapping solutions for real-time robotic applications, and fluency in Python and C++ are essential. Prior experience in sensor fusion and online mapping is highly desirable.

Stack is committed to creating an inclusive workplace where diverse teams can thrive. We believe that a variety of perspectives leads to better ideas and outcomes. Our culture embraces entrepreneurship and innovation across all dimensions of diversity, including gender, race, age, sexual orientation, and more.

In the Staff ML Engineer role at Stack, you will work with advanced technologies including artificial intelligence, robotics, cloud technologies, and machine learning tools. You will also engage with various onboard data sources such as LiDAR, GPS, and cameras to develop advanced mapping algorithms tailored for safety-critical applications in autonomous driving.

At Stack, the work environment is dynamic and collaborative. Whether you are working remotely or from our Pittsburgh office, you'll be part of a team that values innovative thinking and problem-solving. You’ll engage in cross-functional collaboration, leading discussions, and aligning stakeholders to achieve impactful solutions in the field of autonomous systems.

In your response, highlight specific projects where you have designed, trained, or deployed deep learning models. Discuss the challenges you faced, how you overcame them, and any measurable outcomes that demonstrate your expertise in this area.

When answering, elaborate on methodologies you use to optimize performance under constraints, such as computational limits and safety requirements. Detail any relevant experiences where you successfully delivered robust solutions in resource-constrained environments.

Use this opportunity to illustrate your leadership and communication skills. Describe a particular project, the stakeholders involved, and how you facilitated the technical discussions to reach consensus and drive the project forward.

You should define sensor fusion clearly and explain its significance in providing a comprehensive understanding of the driving environment for autonomous vehicles. Share experiences that demonstrate your understanding or application of this concept.

Discuss your prioritization strategies, such as using impact versus effort matrices or agile methodologies. Provide an example where you had to adapt your priorities based on project requirements or stakeholder feedback.

Highlight your analytical skills by discussing how you assessed the existing system, identified bottlenecks, and implemented enhancements. It's crucial to illustrate the positive impact your changes had on the performance or functionality of the system.

Clearly state your proficiency in languages like Python and C++, detailing how you leverage them in projects, including any relevant frameworks or libraries you frequently use to achieve specific goals in machine learning or system design.

Mention specific resources, such as academic journals, online courses, conferences, or communities you engage with to stay informed about the latest trends and technologies. This demonstrates your commitment to continuous professional development.

Discuss essential features like accuracy, real-time processing, and reliability. Evaluate how these features interact and enhance the overall performance of the autonomous system, showing your understanding of the domain’s technical demands.

Express your motivation by aligning your personal and professional goals with Stack's mission and values. Mention specific aspects of their projects or culture that resonate with you, reinforcing your enthusiasm for contributing to their innovative solutions.