Technical Lead Manager, Synthetic Data
Salary not listed • London, United Kingdom • Full-time
Posted 28d ago
About the job
We are seeking a Technical Lead Manager to lead our Synthetic Data team, a critical component of our autonomous driving research. This role will focus on leveraging generative world models, like GAIA-3, to create a production engine for training-grade synthetic data. The goal is to significantly reduce our reliance on expensive on-road data collection by enabling the generation of diverse driving scenarios, even for future vehicle platforms or geographies where data collection is limited. You will lead a team of machine learning engineers, guiding technical strategy, system design, and the development of capabilities that accelerate our journey to AV2.0.
Responsibilities
- Define algorithmic and system design for GAIA generation, synthetic data pipeline, and controllability engine, focusing on efficiency and quality.
- Collaborate with driving-model owners, evaluation, and safety teams to ensure the utility and scalability of generated data.
- Provide mentorship and async review for team members' experimental designs, code, and write-ups.
- Manage direct reports through 1:1s and feedback.
- Stay current with state-of-the-art in video generation, camera transfer, and distillation relevant to model checkpoints and shipping.
- Lead strategic discussions on the synthetic data roadmap, safety case, and platform bring-up sequencing.
- Architect the technical direction for post-training and conditioning world models for synthetic data capabilities.
- Ensure generation, evaluation, and training form a cohesive system from checkpoint to training data artifacts.
- Lead from the front on key components, codebases, and experiments.
- Drive inference optimization, valid-generation rate, and self-serve workflows for synthetic data requests.
- Challenge assumptions and champion bold ideas in synthetic data application.
- Lead a high-performing, cross-functional team of ML engineers and applied scientists.
- Drive quarterly planning and execution in a high-ambiguity environment.
- Align with world-model researchers, platform engineers, driving-model owners, and evaluation teams.
- Manage upwards and laterally to align team goals with company priorities and OEM timelines.
- Grow and structure a resilient team by hiring top talent and designing effective operating models.
- Foster a strong, inclusive culture rooted in scientific rigor, collaboration, and curiosity.
- Coach and mentor team members, tailoring growth plans to individual strengths and aspirations.
- Lead by example through technical engagement and clear feedback.
- Navigate the team through evolving research priorities and fast-moving execution.
Requirements
- 5+ years of experience in ML engineering or applied research roles, with a track record of training and shipping neural networks.
- 4+ years of people management experience, including direct reports and cross-functional project ownership.
- Deep knowledge of generative modeling (diffusion, flow matching, autoregressive, or VAEs) applied to video or other high-dimensional temporal data.
- Hands-on experience with video, generative, or world models (e.g., video generation, novel-view synthesis, neural rendering, controllable generation).
- Working knowledge of cameras and 3D geometry (multi-camera rigs, intrinsics/extrinsics, warps, reprojection) and their impact on generation or downstream training.
- Evidence of closing the loop: taking generated or simulated data into a trained downstream model and measuring impact.
- Experience operating generation or training at scale (multi-GPU jobs, workflow orchestration, large video artifacts) and ensuring reliability.
- Strong Python and PyTorch engineering fundamentals.
- Experience building research-grade production tools.