Senior Staff Software Engineer, TLM

About the Team: The "Oracle" for Autonomous Driving

Our mission is to build the high-fidelity, platform-agnosticGround Truth (GT) enginethat powers the next generation of autonomous vehicle (AV) simulation and evaluation. We function as the "Oracle"-by reprocessing onboard logs offline using state-of-the-art ML Foundation Models, we generate semantic signals that significantly outperform real-time onboard software.

Since our inception in early 2025, we have moved from concept to a fully operational end-to-end ML solution. As we head into 2026, we are scaling this "Oracle" to become the backbone of all large-scale evaluation, enabling the business to test software at a level of rigor and realism previously thought impossible.

The Role

We are looking for a strategic leader to own the Sim GroundTruth landscape. This role sits at the critical intersection of cutting-edge ML research, massive-scale data engineering, and high-stakes product leadership. As a TLM, you will be both a deep technical contributor and a people manager, guiding a high-performing team of ML and Backend engineers to solve the "technical moat" of high-fidelity ML inference at a petabyte scale

Key Responsibilities

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  Scalable ML Architecture & Signal Expansion:Architect a modular, extensible ML framework capable of rapidly absorbing a growing list of complex signal requirements. You will lead the transition from specialized models to unified Foundation Model architectures that maintain "Oracle" quality while scaling to hundreds of new semantic categories.

  
  
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  Strategic Ownership & Quality Leadership:Define the multi-year roadmap for signal quality, coverage, and reliability. Your mandate is to ensure our signals don't just match onboard software-they set the industry benchmark for ground truth accuracy.

  
  
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  Engineering at Extreme Scale:Oversee a pipeline processing millions of segments with a requirement for>99% cache hit rate. You will lead the team in optimizing high-fidelity ML inference costs across massive, petabyte-scale datasets to support rigorous, high-frequency evaluation.

  
  
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  Stakeholder & Ecosystem Growth:Act as the primary interface for "Application Owners" across the company. You will translate complex simulation needs into technical requirements and aggressively grow our customer base to ensure every major software launch is "Oracle-validated."

  
  
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  Operational Excellence:Lead a high-performing team of ML and Backend Engineers, fostering a culture of technical excellence while delivering on mission-critical P0 initiatives.

  
  

Requirements

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  Education:Master's or PhD in Computer Science, Machine Learning, Robotics, or a related field (PhD preferred).

  
  
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  Management Experience:Experience managing and technically leading a team of 10+ Engineers or Research Scientists.

  
  
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  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.

  
  
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  Technical Depth:Hands-on experience with an ability to technically lead ICs daily, including deep knowledge of codebases, eval/data pipelines, and model architectures.

  
  
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  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).

  
  
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  Proficiency:Expert-level skills in Python, Numpy, and deep learning frameworks (PyTorch or JAX).

  
  

Preferred Qualifications

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  Systems Engineering:Experience building and scaling distributed systems or data pipelines at a petabyte scale.

  
  
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  AV Context:Specific experience in Autonomous Driving planning, perception, or simulation research.

  
  
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  Software Rigor:Proficiency inC++and experience with production-grade ML deployment.

  
  
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  Academic Impact:A strong publication record at top-tier conferences (CVPR, ICRA, NeurIPS) or leadership in major open-source projects.