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10 дней назад

Forensics Engineer (Autonomous Driving)

209 700 - 238 250$
Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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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

hirify.global 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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