About the Team: The "Oracle" for Autonomous Driving

Our mission is to build the high-fidelity, platform-agnostic Ground Truth (GT) engine that 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 2027, 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 technical leader to drive the ML perception architecture for Sim GroundTruth. This role sits at the critical intersection of cutting-edge perception ML research, foundation models, and massive-scale offline data engineering. As a Senior Staff Machine Learning Engineer, you will serve as the chief technical authority for our perception models, guiding and mentoring ML engineers to solve the "technical moat" of high-fidelity 3D perception and ML inference at a petabyte scale.

Key Responsibilities

• 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.
• 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.
• ML Scale & Inference Efficiency: Lead the optimization of high-fidelity perception model inference and compute efficiency across massive, petabyte-scale datasets, collaborating with backend infrastructure leads to support rigorous, high-frequency evaluation.
• 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."
• Technical Leadership & Mentorship: Serve as the senior technical leader and mentor for ML perception engineers, championing modeling best practices, architectural rigor, and driving technical execution on mission-critical P0 perception initiatives.

Requirements

• Education: Master’s or PhD in Computer Science, Machine Learning, Robotics, or a related field (PhD preferred).
• Technical Leadership: Proven track record of senior technical leadership setting technical vision, architecting complex ML systems, and mentoring senior engineers and research scientists.
• 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.
• Technical Depth: Hands-on experience with an ability to technically lead ICs daily, including deep knowledge of codebases, eval/data pipelines, and model architectures.
• ML & Perception Expertise: Deep understanding of Foundation Models (VLMs or MMLMs) and computer vision / perception architectures (e.g., Transformers, 3D detection, scene reconstruction), specifically in the context of post-training, fine-tuning, or inference-time scaling.
• Proficiency: Expert-level skills in Python, Numpy, and deep learning frameworks (PyTorch or JAX).

Preferred Qualifications

• Systems Engineering: Experience building and scaling distributed systems or data pipelines at a petabyte scale.
• Object Detection & AV Perception: Deep expertise in 2D and 3D object detection, multi-modal sensor fusion (camera, LiDAR), tracking, and offboard ground-truth generation for autonomous vehicles.
• Software Rigor: Proficiency in C++ and experience with production-grade ML deployment.
• Academic Impact: A strong publication record at top-tier conferences (CVPR, ICRA, NeurIPS) or leadership in major open-source projects.