Meta Reality Labs is seeking an engineer to advance materials research capabilities for next-generation wearables hardware. In this role, you will design, build, and operate the automation backbone of an autonomous materials discovery lab — connecting AI agents, robotic work-cells, and scientific instruments into a seamless, closed-loop pipeline. Working at the intersection of lab automation, agentive AI, and computational materials science, this role translates scientific workflows into production-grade software that compresses a discovery cycle from years into weeks, accelerating the development of novel materials for next-generation wearable devices and robotics.

Automation Engineer, Materials Research Science Responsibilities:

• Define the long-term technical roadmap for laboratory automation systems, integrating robotic sample handling, automated metrology instruments, and data acquisition pipelines
• Architect and own the end-to-end automation infrastructure for high-throughput materials characterization workflows, including optical, mechanical, and electrical property testing of wearable device materials
• Collaborate with scientists, hardware engineers, and product teams to translate experiments and lab workflows into clear integration specifications, data models, and scalable automation solutions
• Work with integrators and vendors to design, build, and commission automated workcells for materials R&D (process development, characterization, property testing, etc.)
• Build and maintain middleware services that connect instruments, robots, and sensors to laboratory information management systems
• Develop instrument drivers and automation scripts that generate command sequences and invoke vendor APIs/SDKs to orchestrate lab workflows end-to-end
• Collaborate with AI and data scientists to tightly integrate the autonomous lab with LLM-based multi-agent systems for experiment planning, analysis, and decision-making
• Design and implement data pipelines that capture, validate, and store experimental metadata to ensure data integrity and reproducibility across the discovery pipeline
• Evaluate and benchmark automation performance — measuring throughput, reliability, error rates, and turnaround time of automated experimental workflows
• Contribute to internal tooling, documentation, and best practices that enable the broader team to leverage automation capabilities
• Drive the adoption of design-of-experiments methodologies and statistical process control within automated materials screening workflows
• Define standards and best practices for automation system reliability, calibration, and data integrity across the materials research organization
• Provide technical guidance to other engineers on automation architecture decisions, instrumentation integration patterns, and software design for laboratory systems
• Evaluate and integrate emerging laboratory automation technologies, robotics platforms, and scientific instrumentation relevant to materials research
  
  

Minimum Qualifications:

• Proficiency in Python, with experience writing production-quality automation and integration code
• Hands-on experience with lab automation platforms (e.g., liquid handlers, robotic arms, automated characterization tools)
• Experience with laboratory information management systems, electronic lab notebooks, or manufacturing execution systems
• Demonstrated ability to translate scientific or manufacturing workflows into reliable, automated processes
• Experience architecting scalable automation platforms for materials characterization or physical science research environments
• Experience with statistical analysis and data pipeline design for high-throughput experimental datasets
  
  

Preferred Qualifications:

• A track record of commissioning or bringing up complex lab, pilot, or manufacturing equipment
• Familiarity with APIs, databases, and enterprise software integration patterns
• Experience defining automation strategy and technical standards at an organizational level within a research or advanced hardware development environment
• Familiarity with computational chemistry or materials science tools (DFT, MD, LAMMPS, ASE) and high-performance computing (HPC) environments
• Experience with retrieval-augmented generation (RAG), knowledge graphs, or scientific literature mining in the context of lab systems
• Publications or demonstrated accomplishments recognized in the field of laboratory automation or materials informatics
• Experience with materials relevant to wearables hardware, such as optical coatings, waveguide materials, display substrates, or flexible electronics
• Experience integrating robotic platforms with laboratory information management systems (LIMS) or material databases
• Experience integrating AI/ML models or LLM-based agent frameworks into physical lab workflows
• Experience with data historians, or real-time supervisory dashboards
• Knowledge of industrial communication protocols
• Familiarity with design-of-experiments frameworks and machine learning approaches applied to accelerated materials discovery
  
  

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].

$184,000/year to $257,000/year + bonus + equity + benefits

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. Learn more about benefits at Meta.