
Robotics Backend & ML Integration Engineer, Site Services
Required skills
- Robotics
- Site Services
- backend systems
- machine learning integration
- data centers
- physical automation
- scalable backend systems
- Python
- web languages
- image processing
Nice to have
- responsible AI practices
- ethical AI practices
- prompt engineering
- context engineering
- agent orchestration
- emerging AI technologies
Role summary
Meta is seeking a Robotics Backend & ML Integration Engineer for its IDC Robotics team. This role focuses on designing, developing, and deploying scalable backend systems and machine learning integrations to enable efficient and safe data center automation. Responsibilities include building data pipelines, developing core backend services, integrating AI models, managing simulation environments, and collaborating with cross-functional teams. The ideal candidate has 5+ years of experience in backend software engineering with a focus on ML integration, proficiency in Python and C++, and knowledge of fault-tolerant architectures and MLOps. Experience with simulation, API design, and mentoring engineers is also required. Preferred qualifications include AI ethics and advanced AI skill development.
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
Minimum Qualifications
- 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
Preferred Qualifications
- 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
- Expertise in one or more of the following areas:
- Familiarity with hardware acceleration and model-infrastructure integration processes
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Track record of contributions to backend software or ML infrastructure communities
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Experience with data analysis tools and collaboration with research and data science teams
- 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
$144,000/year to $204,000/year + bonus + equity + benefits
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