Data Engineer (AI/ML) III - 6253

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.