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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning research and engineering, particularly in generative video and world models, with strong skills in Python and PyTorch. Proven ability to mentor junior researchers and contribute to high-impact publications in the field.
Highest-signal resume keywords
Machine Learning ResearchGenerative Video ModelsPython ProgrammingPyTorch EngineeringDiffusion Models
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Generative ModelingSampling Efficiency ImprovementHigh-Dimensional Data AnalysisModel Throughput OptimizationLatent-Video ModelsReinforcement Learning ArchitecturePerformance OptimizationMetrics DefinitionAblation StudiesClosed-Loop Training Integration
Soft Skills
Collaborative Problem SolvingMentoringFeedback ProvisionInnovative ThinkingInterdisciplinary Teamwork
Tools & Technologies
Research-Grade Production ToolsOpen-Source ML Tooling
Industry Keywords
Spatiotemporal DataMulti-Sensor FusionTechnical RoadmapsPublication RecordInference Latency Reduction
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Set technical direction and design key system components
- Implement and debug new modeling capabilities
- Brainstorm and pair with teammates to solve difficult problems
- Review teammates’ pull requests and experimental designs and provide feedback
- Share findings, align on priorities, and discuss upcoming experiments
- Read and summarize research papers for reading groups
- Invent efficient generative world models using diffusion, transformers, or hybrid approaches
- Architect interactive world models supporting reinforcement learning, planning, and safety evaluation
- Optimize end-to-end performance, including latent compression and context pruning, to reduce inference latency
- Define metrics for long-horizon coherence, physics fidelity, and planner integration
- Run ablations and scaling studies
- Integrate models into closed-loop training and evaluation and measure the sim-to-real gap
- Mentor junior researchers, shape technical roadmaps, publish at top venues, and represent Wayve in the community
- Propose bold ideas and challenge conventional training and evaluation approaches
Requirements
What you’ll need- 4+ years of experience in ML research/engineering focused on generative video and world models
- Deep knowledge of diffusion and latent-video models
- Track record of improving sampling efficiency or model throughput
- Experience with high-dimensional temporal or spatiotemporal data, such as video or multi-sensor fusion
- Strong Python and PyTorch engineering fundamentals
- Experience building research-grade production tools
- Strong publication record or contributions to open-source ML tooling
- Ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment
Benefits
Comp & perks- Meaningful equity, sharing in the ownership and long term success of Wayve
- Relocation support and visa sponsorship where applicable
- Hybrid working and core hours
- Chance to work hands on in vehicle workshops and labs
- Learning and development budgets supporting training, conferences and growth
- Comprehensive health insurance
- Dental benefits
- Enhanced maternity and paternity leave
- Retirement or pension where applicable
- Access to therapists
- Wellbeing partnerships
- Team socials