**Summary:**

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.

**Required Skills:**

Automation Engineer, Materials Research Science Responsibilities:

1. Define the long-term technical roadmap for laboratory automation systems, integrating robotic sample handling, automated metrology instruments, and data acquisition pipelines

2. 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

3. Collaborate with scientists, hardware engineers, and product teams to translate experiments and lab workflows into clear integration specifications, data models, and scalable automation solutions

4. Work with integrators and vendors to design, build, and commission automated workcells for materials R&D (process development, characterization, property testing, etc.)

5. Build and maintain middleware services that connect instruments, robots, and sensors to laboratory information management systems

6. Develop instrument drivers and automation scripts that generate command sequences and invoke vendor APIs/SDKs to orchestrate lab workflows end-to-end

7. 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

8. Design and implement data pipelines that capture, validate, and store experimental metadata to ensure data integrity and reproducibility across the discovery pipeline

9. Evaluate and benchmark automation performance — measuring throughput, reliability, error rates, and turnaround time of automated experimental workflows

10. Contribute to internal tooling, documentation, and best practices that enable the broader team to leverage automation capabilities

11. Drive the adoption of design-of-experiments methodologies and statistical process control within automated materials screening workflows

12. Define standards and best practices for automation system reliability, calibration, and data integrity across the materials research organization

13. Provide technical guidance to other engineers on automation architecture decisions, instrumentation integration patterns, and software design for laboratory systems

14. Evaluate and integrate emerging laboratory automation technologies, robotics platforms, and scientific instrumentation relevant to materials research

**Minimum Qualifications:**

Minimum Qualifications:

15. Ph.D. degree in Electrical Engineering, Computer Science, Mechanical Engineering, Control Engineering, Materials Science, or relevant field, and/or equivalent practical experience

16. 6+ years of experience in lab automation, systems integration, or industrial automation software and/or relevant technical experience

17. Proficiency in Python, with experience writing production-quality automation and integration code

18. Hands-on experience with lab automation platforms (e.g., liquid handlers, robotic arms, automated characterization tools)

19. Experience with laboratory information management systems, electronic lab notebooks, or manufacturing execution systems

20. Demonstrated ability to translate scientific or manufacturing workflows into reliable, automated processes

21. Experience architecting scalable automation platforms for materials characterization or physical science research environments

22. Experience with statistical analysis and data pipeline design for high-throughput experimental datasets

**Preferred Qualifications:**

Preferred Qualifications:

23. A track record of commissioning or bringing up complex lab, pilot, or manufacturing equipment

24. Familiarity with APIs, databases, and enterprise software integration patterns

25. Experience defining automation strategy and technical standards at an organizational level within a research or advanced hardware development environment

26. Familiarity with computational chemistry or materials science tools (DFT, MD, LAMMPS, ASE) and high-performance computing (HPC) environments

27. Experience with retrieval-augmented generation (RAG), knowledge graphs, or scientific literature mining in the context of lab systems

28. Publications or demonstrated accomplishments recognized in the field of laboratory automation or materials informatics

29. Experience with materials relevant to wearables hardware, such as optical coatings, waveguide materials, display substrates, or flexible electronics

30. Experience integrating robotic platforms with laboratory information management systems (LIMS) or material databases

31. Experience integrating AI/ML models or LLM-based agent frameworks into physical lab workflows

32. Experience with data historians, or real-time supervisory dashboards

33. Knowledge of industrial communication protocols

34. Familiarity with design-of-experiments frameworks and machine learning approaches applied to accelerated materials discovery

**Public Compensation:**

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

**Industry:** Internet

**Equal Opportunity:**

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 accommodations-ext@meta.com.