Senior Engineering Manager (AI/ML)

TL;DR

Senior Engineering Manager (AI/ML): Leading a team of ML Engineers in the development of AI/ML technology for primary care physicians with an accent on technical solutioning, roadmap building, and aligning AI-enabled workflows in healthcare settings. Focus on designing and implementing secure, scalable AI/ML platform architectures, MLOps principles, and translating business objectives into technological roadmaps.

Location: Remote (United States)

Company

hirify.global empowers primary care physicians with technology to keep their patients healthy, preventing unnecessary hospitalizations.

What you will do

• Build and nurture a high-performing engineering team.
• Provide strong technical leadership, driving solutioning and roadmaps for ML/AI projects.
• Set clear goals and remove roadblocks for team achievement.
• Collaborate seamlessly with stakeholders across hirify.global to achieve business outcomes.
• Drive engineering excellence in processes and systems with other engineering leaders.

Requirements

• BS/BTech (or higher) in Computer Science, Engineering, or a related field.
• 10+ years of production-level experience as an engineer and technical lead building highly scalable and reliable software.
• 5+ years of managerial experience building and leading technical engineering teams.
• 7+ years of experience in machine learning related technologies, with a strong preference for Python.
• Extensive experience in designing and implementing secure, scalable, and maintainable AI/ML platform architectures.
• Proficiency in distributed systems, microservices, containerization technologies (e.g., Docker, Kubernetes), model training infrastructure, orchestration tools, and MLOps principles.

Nice to have

• Experience in attracting, hiring, and coaching world-class engineers.
• Experience in taking ownership of technology decisions while delegating and empowering team members.
• Strong communication and relationship-building skills, with experience influencing multiple stakeholders.
• Familiarity with current AI/ML research trends and ability to translate advancements into practical healthcare applications.
• Proven track record of mentoring and developing AI/ML talent.
• Understanding of the fast-paced, dynamic environment of a startup.

Hiring process

• Application materials may be organized and evaluated using automated AI tools.
• Human judgment plays an essential role in the hiring process.