Engineering Manager, Rad AI

• 6+ years of experience in software engineering, with at least 3+ years focusing on ML infrastructure
• 2+ years of experience leading technical teams
• Working knowledge of advanced model customization and fine-tuning methodologies
• Experience deploying and operating production ML systems at scale
• Proficiency with Python and at least one infrastructure-as-code tool (Terraform, CloudFormation, etc.)
• Strong communication skills with the ability to translate complex technical concepts across teams
• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• Passion for applying AI to meaningful problems with direct impact on patient care

Desirable

• Our Gen AI Engineering team is pushing the boundaries of what's possible with large language models (LLMs) and advanced model customization
• This is a unique opportunity to work at the intersection of AI and healthcare, where your technical leadership will directly contribute to reducing radiologist burnout and improving patient care
• You will tackle the unique challenges of scaling AI in healthcare, including compliance, data privacy, and model robustness across diverse products
• This role reports to the VP of Engineering and your work will be highly visible across the company
• You'll have significant autonomy, work with our team of healthcare and AI experts, and directly influence our technical strategy as we expand our reach across healthcare systems nationwide
• If you're passionate about operationalizing AI at scale and building systems that have meaningful impact, this role is for you
• Lead and mentor a growing team of Gen AI engineers, helping them develop professionally while tackling healthcare's most challenging AI problems
• Pioneer new approaches to healthcare-specific LLM deployment that balance clinical accuracy, performance, and regulatory requirements
• Define and execute the long-term Gen AI engineering strategy, balancing performance, cost, and reliability across healthcare AI applications
• Drive innovative training and inference architectures that can scale to support thousands of radiologists simultaneously
• Collaborate with radiologists and ML researchers to translate clinical insights into technical solutions that meaningfully improve patient care
• Establish technical partnerships with leading AI infrastructure providers to optimize our unique healthcare AI compute requirements
• Champion a culture of technical excellence, continuous learning, and ethical AI development