10 дней назад
Forensics Engineer (Autonomous Driving)
209 700 - 238 250$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Forensics Engineer (Autonomous Driving) (Robotics/AI): Investigating issues across the full Wayve autonomous vehicle stack, from on-road fleet data and vehicle systems to software and models, with an accent on root cause analysis, data-driven experimentation, and safety. Focus on reproducing incidents through simulation, automating investigation workflows, and translating findings into improvements across engineering, model development, operations, and safety teams.
Location: Sunnyvale, California, USA (hybrid)
Salary: $209,700–$238,250 per year, plus a competitive equity package.
Company
develops autonomous driving technology and operates a mission-driven, fast-moving organization focused on self-driving vehicles.
What you will do
- Investigate on-road data and recurring issues across the full autonomous vehicle stack, including the robot, models, and software.
- Perform root cause analysis, identify fleet-wide patterns, and establish what happened during on-road incidents.
- Analyze data and communicate findings through dashboards and visualizations to support clear decisions.
- Collaborate with engineering, model development, operations, and safety teams, including taking rides in autonomous vehicles.
- Develop automated workflows and investigation playbooks to accelerate testing and issue resolution.
- Use simulation and offline tools to reproduce, debug, and resolve issues while reducing reliance on fleet resources.
Requirements
- Ability to work from Sunnyvale, California, USA in a hybrid arrangement.
- 3+ years of experience working with complex robotics, autonomous vehicle, or comparable engineered systems.
- Strong critical thinking, problem-solving, and systems-thinking skills across hardware, software, and machine learning models.
- Experience designing real-world experiments to test hypotheses and writing Python for data analysis and varied analytical use cases.
- Clear communication skills for explaining complex technical problems to technical and non-technical stakeholders.
- Safety-conscious approach, with experience identifying safety implications and influencing decisions through evidence and findings.
Nice to have
- Experience applying and evaluating machine learning models.
- Experience with safety-critical systems or the automotive, robotics, and AI industries.
- Experience promoting statistical rigor and experimental best practices.
- Experience in a fast-moving technology company or startup.
Culture & Benefits
- Hybrid working with time in offices and workshops alongside work from home.
- Core working hours with flexibility determined by each team.
- Competitive compensation, equity, private health insurance, and support for formal learning.
- Onsite chef, workplace nursery scheme, cycle scheme, therapy, yoga, onsite bars, and social budgets.
- Ego-free, respectful, and welcoming work environment.
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