5 дней назад
Automation Engineer (Robotics)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Automation Engineer (Robotics): Improving the reliability and performance of deployed autonomous robots through failure triage, ML datasets, model evaluation, and production deployment with an accent on robotics, machine learning, and field operations. Focus on diagnosing perception, prediction, and planning failures, training and fine-tuning models, and validating improvements across real-world sites.
Location: Irvine, California, United States; on-site
Company
develops risk-aware, field-ready embodied AI systems for real robots, sensors, and real-world deployments.
What you will do
- Own day-to-day triage of issues across deployed robot sites and identify high-impact failure modes.
- Analyze robot behavior, logs, telemetry, and model outputs across perception, prediction, and planning.
- Build datasets and evaluation sets for new failure modes and site-specific use cases.
- Train, fine-tune, and evaluate machine learning models when needed to address production challenges.
- Partner with data, modeling, deployment, and robotics teams to integrate, validate, and ship improvements.
- Support new use cases and customer requirements from development through production deployment.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Robotics, AI, or a related field.
- Strong Python skills and experience with modern machine learning frameworks such as PyTorch.
- Experience training, fine-tuning, and evaluating machine learning models.
- Strong debugging and problem-solving skills across machine learning and robotics systems.
- Experience with C++ and production machine learning or robotics systems.
- Understanding of machine learning data pipelines, labeling, evaluation, and model deployment.
Nice to have
- Experience with real-world robotics, autonomous vehicles, or deployed machine learning systems.
- Experience with perception, prediction, planning, or learned navigation models.
- Experience diagnosing model failures and driving iterative improvements from production data.
Culture & Benefits
- Work directly with real robots, sensors, and field deployments.
- Collaborate across robotics, machine learning, data, labeling, modeling, and deployment teams.
- See engineering improvements tested on hardware and deployed to production sites.
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