Pay Range: $85hr - $90hr

• Bachelor's degree or higher in Computer Science, Software Engineering, Data Science, Biomedical Engineering or related field.
• 6+ Years of relevant work experience with Bachelor's degree.
• 3+ Years of relevant work experience with Masters or PhD.
• 4+ years of consistent coding in Python.
• Strong understanding and use of relational databases and clinical data models.
• Experience working with medical imaging data (DICOM) computer vision algorithms and tools.
• Experience with AWS and cloud technologies and AWS DevOps tools.
• Experience with creating and managing CI/CD pipelines in AWS.
• Experience with Infrastructure as Code (IaC) using Terraform, CloudFormation or AWS CDK.
• Excellent organizational, communication, and collaboration skills.
• Foundational knowledge in machine learning (ML) operations and imaging ML pipelines.

• Experience with software validation in a regulated industry
• Experience with Cloud imaging tools (ex. AWS Health Imaging, Azure Health Data Services)
• Working knowledge of data de-identification/pseudonymization methods
• Manipulating tabular metadata using SQL and Python's Pandas library
• Experience with the Atlassian Tool Chain
• Data and annotation version control tools and processes
• Knowledge of HIPAA, FDA regulations (21 CFR Part 11), GDPR for medical device data governance.

• Design a systems level architecture for clinical, device, and imaging data and pipelines to support machine learning & classical algorithm development throughout the product lifecycle.
• Ensure architecture supports high-throughput image ingestion, indexing, and retrieval.
• Advance conceptual, logical, and physical data models for structured, semi- structured, and unstructured data.
• Help define and document data standards and definitions.
• Implement governance frameworks that enforce healthcare and data regulations to data architecture (HIPAA, FDA Part 11, GDPR, etc.).
• Performs strategic validation tasks of data management tools and platforms
• Collaborate closely with data scientists, cloud data engineers, algorithm engineers, clinical engineers, software engineers and systems engineers locally and globally.
• Investigate, research, and recommend appropriate software designs, machine learning operations, tools for dataset organization, controls, and traceability.
• In all actions, lead with integrity and demonstrate a primary commitment to patient safety and product quality by maintaining compliance to all documented quality processes and procedures.