机器人后端与机器学习集成工程师，站点服务

Meta（Meta Platforms）岗位：Robotics Backend & ML Integration Engineer, Site Services Responsibilities

Build and maintain high-throughput pipelines for image, video, and time-series data to support robotics applications

Develop core backend services, triage issues, execute bug fixes, and implement long-term design improvements

Benchmark classical, modern AI, and hybrid techniques to integrate optimal solutions into production services

Fine-tune foundation models on proprietary datasets, benchmark performance, and manage deployment workflows for inference

Communicate technical trade-offs and drive backend architecture decisions with cross-functional teams

Support and manage scalable simulation stacks and environments for robotic testing and synthetic data generation

Integrate internal and external systems via APIs, agent-based workflows, standardized AI context protocols, and secure authentication layers

Build bridge layers connecting backends to web components with robust failure-mode handling and fallbacks

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Bachelor’s degree in Computer Science, Software Engineering, Robotics, Electrical Engineering, or a related technical field

5+ years of experience in C++ and Python, focusing on the design, development, and integration of backend services and ML inference pipelines

Demonstrated experience developing high-throughput backend data pipelines for image, video, and time-series data streams

Strong knowledge of fault-tolerant backend architectures, model serving platforms, inference optimization, and MLOps orchestration tools

Hands-on experience with web frameworks, API design, security protocols, and integration layers used to serve ML inference

Proven ability to evaluate, benchmark, and integrate open-source and third-party AI, classical, or hybrid software solutions into production

Experience navigating ambiguous technical requirements, resolving complex system issues, and executing long-term architectural improvements

Strong collaboration skills with cross-functional engineering teams, researchers, and external vendors to deliver production-ready software

Experience managing simulation stacks, hardware/software bridge layers, and continuous integration workflows for complex technical systems

Track record of mentoring engineers, driving technical best practices, and improving engineering tooling and process

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Master’s degree or above in Computer Science, Machine Learning, Robotics, Electrical Engineering, or a related field

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Demonstrated ability to scale backend solutions, with a focus on fault tolerance and reliability

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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Individual compensation is determined by skills, qualifications, experience, and location.

Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable.

In addition to base compensation, Meta offers benefits.

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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

5+ years of experience in C++ and Python, focusing on the design, development, and integration of backend services and ML inference pipelines.