Data & Analytics Jobs in Redmond, WA (Now Hiring) — 358 open

Data Engineer (AI/ML) III

itD is seeking a Data Engineer (AI/ML) III to drive the development of machine learning solutions and scalable data processing pipelines that enhance the visual quality, performance, and reliability of next-generation AR display systems within Reality Labs Hardware. The ideal candidate will bring deep expertise in machine learning, computer vision, image and signal processing, and large-scale data engineering, along with a proven track record of delivering production-ready ML algorithms, automated analytics pipelines, and data-driven insights for hardware systems.

 

Location: On-site in Redmond, WA. Candidates may also be based in Sunnyvale, CA. Strong remote candidates will be considered if located within ±3 hours of the Redmond, WA time zone.

Pay Rate: $50 - $54 per hour, depending on experience.

Duration: 12 months

We provide comprehensive medical benefits, a 401(k) plan, paid holidays, and more.
Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.

Responsibilities

• Own end-to-end data processing pipelines for display characterization data, including sensor images, metrology measurements, and manufacturing yield data.
• Develop machine learning and AI algorithms to detect, classify, and analyze visual artifacts, display defects, and performance anomalies.
• Build automated analysis tools for disparity sensor evaluation, including SNR estimation, pattern detection accuracy, and ambient cross-talk assessment.
• Design and implement anomaly detection models to identify display performance regressions across manufacturing and integration testing.
• Create dashboards and visualization tools to communicate display quality metrics and engineering insights to cross-functional hardware teams.
• Develop image processing algorithms for waveguide characterization, including uniformity analysis, efficiency mapping, and defect detection.
• Collaborate closely with optical, process, and integration engineers to translate hardware requirements into scalable algorithmic solutions.
• Maintain and enhance data infrastructure supporting machine learning workflows, including data collection, storage, versioning, and accessibility.
• Document methodologies, validate model performance against ground truth, and contribute to reproducible engineering practices.

Internal Responsibilities

• Attend regular internal practice community meetings.
• Collaborate with your itD practice team on industry thought leadership.
• Complete client case studies and learning material (blogs, media material).
• Build out material to contribute to the Digital Transformation practice.
• Attend internal itD networking events (in person and virtual).
• Work with leadership on career fast-track opportunities.

Required Qualifications and Skills

• M.S. or Ph.D. in Electrical Engineering, Computer Science, Optical Engineering, Applied Physics, or a related quantitative field.
• 3+ years of experience developing ML/AI algorithms for image processing, signal processing, or sensor data analysis.
• Strong proficiency in Python.
• Hands-on experience with PyTorch.
• Experience with computer vision techniques including feature detection, segmentation, classification, and pattern matching.
• Proven experience building and maintaining large-scale data processing pipelines for experimental or manufacturing data.
• Experience with statistical analysis, hypothesis testing, and experimental design.
• Strong understanding of anomaly detection and machine learning model development.
• Experience presenting technical findings to cross-functional engineering teams.

Preferred Qualifications and Skills

• 5+ years of industry experience in optics, display systems, semiconductor manufacturing, or hardware characterization.
• Experience with display metrology including MTF, luminance uniformity, chromaticity, and contrast measurements.
• Knowledge of sensor characterization including SNR analysis, noise modeling, and dynamic range assessment.
• Experience developing deep learning models for defect detection or anomaly classification in manufacturing environments.
• Familiarity with AR/VR display technologies including waveguides, micro-LEDs, LCoS, and holographic optical elements.
• Experience with optical system modeling or ray-tracing concepts.
• Experience with data visualization tools such as Plotly, Matplotlib, or Tableau.
• Experience using Git and CI/CD pipelines in collaborative development environments.
• Previous experience supporting Reality Labs, Meta, or similar hardware-focused organizations.

Education

• Master's or Ph.D. in Electrical Engineering, Computer Science, Optical Engineering, Applied Physics, or a closely related engineering discipline.