LEAD Computer Scientist - LEAD Engineer - SR. Computer Scientist - Medical AI Software Engineering

Overview

LEAD COMPUTER SCIENTIST - LEAD ENGINEER - SR. COMPUTER SCIENTIST - Medical AI Software Engineering. The role involves leading architecture and design for large-scale medical AI software systems and platforms, applying advanced ML/AI techniques, and shaping solutions for diverse applications in collaboration with engineers, researchers, and external partners.

• Lead architecture and design for complex, large-scale medical AI software systems and platforms for SwRI clients.
• Design and implement scalable, reliable, and efficient systems by integrating advanced system engineering and ML Ops practices.
• Drive technical strategy for the application of modern and traditional machine learning algorithms in decision support systems.
• Identify and architect opportunities to extend automation and AI solutions into new industries and applications.
• Mentor engineering and research staff, raising the technical bar across projects.
• Work closely with engineers, researchers, and external partners to shape solutions that are flexible, modular, and adaptable to diverse applications.
• Foster innovation by integrating cutting-edge ML Ops techniques into the overall system architecture, ensuring seamless model deployment and monitoring.

• Define and oversee system and software architecture for advanced AI-enabled platforms, ensuring scalability, security, and compliance with medical and government standards.
• Partner with researchers and engineers to guide implementation of ML/AI software solutions and ensure alignment with system-level requirements.
• Collaborate with clients and stakeholders to shape requirements into technical roadmaps and proposals. Develop and maintain infrastructure for CI/CD pipelines tailored for machine learning model versions, experimenting with new frameworks and tools to optimize operations.
• Provide technical leadership across multiple concurrent projects, ensuring quality, performance, and maintainability. Implement robust monitoring and alerting mechanisms to ensure the reliability and performance of deployed ML models.
• Establish development best practices, including CI/CD, code quality standards, and security compliance. Stay current with emerging AI technologies and evaluate integration into existing platforms.

• Requires a Bachelors, Masters or a PhD in Computer Science, Data Science, Software Engineering, Data Engineering, Computer Engineering or Electrical Engineering.
• 8+ years:
  Proven experience in ML Ops, including model deployment, CI/CD pipelines, model versioning, monitoring, and lifecycle management.
• 3 years:
  Experience in a technical leadership or software architecture role.
• Deep expertise in software architecture for distributed systems, AI/ML platforms, and cloud-native environments. Strong proficiency in Python and modern development practices (Git, CI/CD, Agile). Strong foundation in systems engineering principles, with the ability to design an
• Experience with SQL/No
  
  SQL databases, containerization (Docker, Kubernetes), and microservices architecture. Experience architecting systems with regulatory and security constraints (HIPAA, DoDI 8500.1, FedRAMP).
• Familiarity with modern front-end frameworks (React.js, Flutter) and decision-support tool development. Demonstrated ability to lead teams, mentor engineers, and engage directly with clients at executive and technical levels.
• A valid/clear driver's license is required.

Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information. Applicant must be a U.S. citizen.

Job Location s:
San Antonio, Texas