Senior Applied Scientist - Computer Vision for Quantum

Requirements

• Master’s or Doctorate degree in Computer Science, Physics, Electrical Engineering, Applied Mathematics, Statistics, Data Science, or a related field OR equivalent experience
• Programming experience in Python, including scientific computing and development of production-quality code (testing, packaging, version control, and code review)
• Experience with image processing, computer vision, or imaging-based analysis workflows
• Demonstrated expertise in statistical analysis and uncertainty estimation in measurement or experimental systems

Nice to Haves

• Experience developing, training, validating, and deploying machine learning models for experimental or production data
• Experience building and maintaining data pipelines in modern distributed or analytics environments (e.g., Spark, Databricks, Delta Lake, or equivalent)
• Familiarity with nanofabrication processes and associated metrology techniques
• Experience working in shared, long-lived analytical or production codebases
• Experience collaborating with experimental, hardware, or scientific teams and reasoning about physical system constraints

What You'll Be Doing

• Develop and maintain scalable analysis pipelines and agentic workflows for experimental microscopy imaging and characterization data
• Design and implement algorithms for image analysis, registration, feature extraction, and quantitative metrics
• Build and operationalize machine learning and AI models for feature extraction, classification, regression, or anomaly detection
• Partner with physicists, hardware engineers, materials scientists, and data engineering teams to translate experimental data
• Design and maintain clear, interpretable data models and datasets
• Own the quality, reliability, and documentation of analytical workflows

Perks and Benefits

• Ability to leverage AI tools to drive innovation and efficiency
• Ability to work in an “AI-first” environment using modern AI tools to accelerate discovery through hardware development