Principal Software Engineer, Team Lead - Perception Platforms

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Software Engineer, Team Lead - Perception Platforms based in the United States. The Principal Software Engineer, Team Lead - Perception Platforms will lead the development of critical machine learning infrastructure that enables autonomous vehicles to understand and navigate the world around them. This senior technical leadership role sits at the intersection of ML infrastructure, perception systems, and large-scale data engineering. You will lead a high-performing team responsible for building and optimizing data pipelines, model training workflows, evaluation frameworks, and visualization tools. Working closely with machine learning engineers and research scientists, you will help accelerate development from experimentation through deployment and ongoing improvement. You will shape technical strategy, mentor engineers, and drive engineering excellence while remaining actively involved in production-level coding. This is an opportunity to contribute to advanced autonomous driving technology with the potential to improve transportation safety, accessibility, and reliability.

Build, lead, and manage a high-performing engineering team responsible for developing, maintaining, and optimizing data, training, and evaluation pipelines for perception models. Define team objectives, technical priorities, and roadmaps aligned with broader organizational goals and product development needs. Provide technical guidance, mentorship, and career development support to engineers, fostering a culture of collaboration, accountability, and continuous learning. Partner closely with machine learning engineers and research scientists to identify technical challenges and improve the efficiency, scalability, and performance of ML workflows. Contribute directly to the design and implementation of high-quality, production-ready software across shared codebases. Architect and optimize end-to-end machine learning development workflows, from data preparation and model training to evaluation, deployment, and maintenance. Develop and improve large-scale data pipelines that support the transformation, processing, and management of datasets used by on-vehicle and off-vehicle perception systems. Build and maintain evaluation frameworks and visualization tools that provide insights into dataset distributions, model behavior, system performance, and edge cases. Advance active learning workflows that identify and incorporate high-value data to improve model accuracy and robustness over time. Lead technical design discussions, code reviews, testing practices, and engineering standards to ensure software quality, maintainability, and reliability. Encourage cross-functional collaboration and alignment across engineering, ML research, and other relevant teams. Evaluate and introduce technologies and methodologies that accelerate machine learning development and improve operational efficiency. Support the delivery of complex technical initiatives through effective planning, execution, and communication. Requirements: At least 7 years of professional software engineering experience, including 3 or more years in formal or informal technical leadership, mentoring, or team leadership. At least 2 years of experience developing, operating, or supporting distributed machine learning training across clusters of GPU nodes. Bachelor's or master's degree in Computer Science or a related technical discipline. Strong commitment to remaining hands-on, with a proven ability to contribute high-quality, production-level code to shared software projects. Proficiency in Python and familiarity with data processing libraries such as NumPy and Pandas. Extensive backend development experience and a demonstrated ability to design and lead the architecture of complex software systems. Strong understanding of machine learning or perception systems, with the ability to guide the development of supporting infrastructure and tooling. Demonstrated experience designing and delivering data visualization tools, internal dashboards, or engineering interfaces that support data-driven decisions. Expert knowledge of software engineering principles, including software design, source control, build processes, code reviews, and testing methodologies. Proven ability to lead and mentor engineers, establish technical direction, and promote engineering best practices. Excellent communication and interpersonal skills, with the ability to articulate a technical vision, collaborate across disciplines, and motivate a team. Expertise in concurrency, parallel processing, and database systems is a plus. Experience with distributed computing frameworks such as Kubernetes (K8s) and Ray is preferred. Experience developing and deploying perception systems for autonomous vehicles or robotics is highly desirable. A PhD in a relevant field, or equivalent industry experience demonstrating continued technical development, is an advantage. Proficiency in modern C++, including C++14, C++17, or later, is beneficial. Experience building products using contemporary large language models (LLMs) and Model Context Protocol (MCP) is a plus. Familiarity with GPU-accelerated data processing and machine learning frameworks such as PyTorch or TensorFlow is desirable. Strong project management skills and a track record of successfully delivering complex technical projects. Benefits: Estimated annual base salary: $240,000–$330,000 USD, depending on skills, experience, expertise, location, and other relevant factors. Potential additional compensation through bonuses and/or company equity. Medical, dental, and vision insurance for eligible employees. 401(k) retirement plan with company matching. Health Savings Account (HSA) options. Life insurance. Pet insurance. Additional employee benefits, depending on eligibility. Work location options that include remote work within the United States, as well as opportunities associated with Boston, Las Vegas, and Pittsburgh. The opportunity to lead a technically advanced team working on machine learning infrastructure, robotics, and autonomous vehicle perception. A collaborative, multidisciplinary environment focused on innovation, professional development, and meaningful technological impact. The opportunity to contribute to technology designed to improve road safety, transportation accessibility, and mobility.