Senior Staff Software Engineer (TLM)

Join our team as a Senior Staff Software Engineer (TLM) and take ownership of the Sim GroundTruth landscape. This strategic leadership role combines cutting-edge ML research, massive-scale data engineering, and high-stakes product leadership. You will architect a modular ML framework, define the multi-year roadmap for signal quality, oversee a pipeline processing millions of segments, act as the primary interface for application owners, and lead a high-performing team of ML and Backend Engineers. Enjoy a comprehensive benefits package, including medical, dental, and vision insurance, competitive compensation, and a hybrid work model.

• Architect a modular, extensible ML framework capable of rapidly absorbing a growing list of complex signal requirements.
• Define the multi-year roadmap for signal quality, coverage, and reliability, ensuring signals set the industry benchmark for ground truth accuracy.
• Oversee a pipeline processing millions of segments with a requirement for >99% cache hit rate, leading the team in optimizing high-fidelity ML inference costs.
• ML Expertise: Deep understanding of Foundation Models (LLMs, VLMs, or MMLMs), specifically in the context of post-training, fine-tuning, or inference-time scaling (e.g., MCTS, Chain-of-Thought)
• Education: Master’s or PhD in Computer Science, Machine Learning, Robotics, or a related field (PhD preferred)
• Management Experience: Experience managing and technically leading a team of 10+ Engineers or Research Scientists
• Technical Depth: Hands-on experience with an ability to technically lead ICs daily, including deep knowledge of codebases, eval/data pipelines, and model architectures
• Cross-Stakeholder Alignment: Proven track record of navigating complex organizations to gather requirements from diverse customers and aligning them into a unified technical roadmap. You can negotiate Roles & Responsibilities (R&R) across competing priorities
• Proficiency: Expert-level skills in Python, Numpy, and deep learning frameworks (PyTorch or JAX)
• Systems Engineering: Experience building and scaling distributed systems or data pipelines at a petabyte scale
• AV Context: Specific experience in Autonomous Driving planning, perception, or simulation research
• Academic Impact: A strong publication record at top-tier conferences (CVPR, ICRA, NeurIPS) or leadership in major open-source projects
• Software Rigor: Proficiency in C++ and experience with production-grade ML deployment