pythonkubernetesmlopsmachine learningdistributed systemsreinforcement learningroboticsalgorithm development
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Вакансия предлагает значимую работу на стыке робототехники и промышленного ИИ, с понятными задачами и современным стеком. Без указанной зарплаты сложно оценить компенсацию для senior-специалиста в США.
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Текст:
Hirify AI/Оригинал
TL;DR
Principal Architect (AI/ML): Leading the design and evolution of a Multi-Agent Path Finding algorithm and scalable robotic navigation capabilities with an accent on machine learning pipelines, reinforcement learning, and distributed systems. Focus on deploying and monitoring production ML models, integrating continuous learning with robotic orchestration engines, and solving real-time multi-agent optimization challenges.
Location: Redwood City, California, United States; onsite role
Company
hirify.global develops AI-driven robotic automation software and hardware for distribution, fulfillment centers, and retail operations.
What you will do
Define the technical roadmap for performance and scalability in robotic navigation.
Lead the design and implementation of machine learning pipelines covering data ingestion, training, validation, deployment, and monitoring.
Own production deployment of machine learning and reinforcement learning models using MLOps platforms such as Vertex AI.
Integrate machine learning pipelines with robotic orchestration engines to enable continuous learning and adaptation.
Collaborate with software, robotics, product, and operations teams to address fulfillment challenges.
Requirements
10+ years of experience in academia or industry.
Master’s or Ph.D. in Computer Science, AI/ML, or a related field.
Strong knowledge of path planning, graph search, optimization for multi-agent systems, machine learning, deep learning, and reinforcement learning.
Production experience with ML models, MLOps, model CI/CD, pipeline orchestration, and monitoring.
Proficiency in Python and experience with TensorFlow or PyTorch.
Experience with distributed systems, microservices, Docker, Kubernetes, concurrency, parallelism, real-time systems, event-driven architecture, GCP, and Vertex AI.
Nice to have
Familiarity with Erlang, Elixir, or other concurrency-first functional programming languages.
Open-source contributions, research publications, or patents in MAPF, reinforcement learning, or distributed AI systems.
Culture & Benefits
Work within the GreyMatter Engineering department and Advanced Automation unit.
Full-time employment.
Equal employment opportunity across legally protected characteristics.
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