Technical Lead Manager, Synthetic Data

Technical Lead Manager role leading the Synthetic Data team within Simulation at Wayve. The team works to reduce dependency on on-road data collection by turning generative world models (such as GAIA-3) into a production engine for training-grade experience. The role leads a high-performing team of machine learning engineers and applied scientists, sets technical direction for world-model post-training and synthetic data generation, and owns the end-to-end generation, evaluation and training loop. Interview process: initial recruiter screen (30 mins), competency interviews (Programming/PyTorch debugging and hiring manager interview; 2 hours total), deep-dive technical interviews (Systems and domain-specific; 3 hours total), and final mission and values interview (45 mins).

Responsibilities

Define approach to GAIA generation and system design of the synthetic data pipeline and controllability engine; Collaborate with driving-model owners, evaluation and safety teams on utility and scalability of generated data; Review teammates' experimental designs, PRs, and ablation write-ups and give direct feedback; Manage direct reports through 1:1s and feedback; Keep up to date with state of the art in video generation, camera transfer and distillation; Lead or join strategic discussions on the synthetic data roadmap, safety case and platform bring-up sequencing; Set technical direction for post-training and conditioning world models for synthetic-data capabilities (rig transfer, pose transfer, controllability); Keep generation, evaluation and training as one system with reproducible lineage; Drive inference optimisation, valid-generation rate, and self-serve workflows for model developers; Lead a cross-functional team of ML engineers and applied scientists; Drive quarterly planning and execution; Hire, structure and grow the team; Coach and mentor team members

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 modelling (diffusion, flow matching, autoregressive, or VAEs) applied to video or other high-dimensional temporal data; Hands-on experience with video, generative or world models, for example video generation, novel-view synthesis, neural rendering, or controllable generation; Working knowledge of cameras and 3D geometry (multi-camera rigs, intrinsics/extrinsics, warps and reprojection) and why they break generation or downstream training; Evidence of closing the loop: taking generated or simulated data into a trained downstream model and measuring impact through mix ratios, ablations and failure analysis; Experience operating generation or training at real scale, including multi-GPU jobs, workflow orchestration, large video artefacts, and making that path reliable; Strong Python and PyTorch engineering fundamentals, and experience building research-grade production tools; Excellent communication skills and a passion for coaching and mentoring others; Balance technical depth with people leadership; Embrace ambiguity and help the team make sense of it, keeping clarity and momentum through uncertainty

Benefits

Meaningful equity; Relocation support and visa sponsorship where applicable; Hybrid working, core hours and hands-on work in vehicle workshops and labs; Learning and development budgets for training, conferences and growth; Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials; Salaries benchmarked against the market annually