Machine Learning Engineer, Infrastructure

About Rad AI
Rad AI is a pioneering healthcare technology company dedicated to transforming the medical imaging landscape through the power of artificial intelligence. Founded by a radiologist, Rad AI leverages extensive proprietary datasets and advanced AI algorithms to enhance diagnostic accuracy, streamline workflows, and reduce radiologist burnout. Our innovative solutions are designed to support radiologists in delivering faster, more accurate diagnoses, ultimately improving patient outcomes. With a strong focus on research and development, Rad AI has established itself as a leader in healthcare AI, securing over $140 million in funding and forming strategic partnerships with major healthcare providers across the United States.
Our AI-driven platform is utilized daily by thousands of radiologists, supporting a significant portion of medical imaging in the US. Recognized for our innovation and growth, Rad AI has received accolades from CB Insights, AuntMinnie, and Deloitte, and was recently named to CNBC’s Disruptor 50 list. Our commitment to advancing healthcare through technology is reflected in our rapid growth, cutting-edge research, and dedication to making a meaningful impact on millions of lives.
About The Role
We are seeking a highly skilled Staff Machine Learning Engineer to join our MLOps team. In this role, you will be instrumental in designing, developing, and maintaining the infrastructure that powers our AI research and production systems. Your work will directly influence how our models are trained, deployed, and integrated into clinical workflows, supporting radiologists and healthcare providers across the country. This position offers a unique opportunity to work at the intersection of AI, healthcare, and cloud technology, contributing to innovations that improve diagnostic accuracy and patient care.
The ideal candidate will have a strong background in backend development, cloud-native architectures, and machine learning systems. You will collaborate closely with data scientists, product managers, and engineering teams to build scalable, secure, and resilient infrastructure. Your expertise will help accelerate our model development lifecycle, enhance system observability, and ensure compliance with healthcare regulations such as HIPAA. This role is primarily backend-focused, with development primarily in Python, and offers the chance to shape the future of AI-driven healthcare solutions.
Qualifications

• 8+ years of industry experience in machine learning engineering within cloud-native environments
• Proficiency in Python programming
• Experience with infrastructure and DevOps tools such as Kubernetes, Docker, and Ansible
• Strong knowledge of cloud platforms such as AWS, GCP, or Azure
• Experience architecting distributed systems, storage solutions, and databases
• Hands-on experience with machine learning frameworks like PyTorch and LangGraph
• Knowledge of orchestration tools such as Airflow (preferred)
• Familiarity with infrastructure-as-code tools like Terraform, Pulumi, or CloudFormation
• Experience with monitoring, logging, and tracing tools such as Cloudwatch, NewRelic, or Grafana
• Excellent communication skills and a systematic approach to problem-solving
• Proven ability to manage incidents and implement preventative systems through blameless postmortems

Responsibilities

• Design and architect the infrastructure supporting machine learning applications, services, and workflows
• Develop and maintain the ML platform supporting continuous integration, delivery, and training
• Create cloud-native services and serverless architectures to ensure scalability and resilience
• Collaborate with data scientists to develop data pipelines for production machine learning models
• Write secure, maintainable, and high-quality code adhering to internal standards and best practices
• Deploy, monitor, and optimize the full ML platform stack, including observability and data analytics
• Integrate backend systems with customer-facing products and support the full lifecycle of model research and deployment
• Work closely with cross-functional teams to iterate on features and improve infrastructure efficiency
• Lead incident management efforts, perform root cause analysis, and implement preventative measures

Benefits

• Comprehensive medical, dental, and vision insurance
• Life insurance coverage
• Health Savings Account (HSA) with employer match, Flexible Spending Account (FSA), and DCFSA
• 401(k) retirement plan with company matching
• 11 paid company holidays annually
• Flexible remote work policy and location flexibility
• Generous PTO policy to support work-life balance
• Annual company-wide offsite and periodic team gatherings
• Annual equipment stipend to support remote work setup

Equal Opportunity
Rad AI is committed to fostering an inclusive and diverse workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. We consider qualified applicants with criminal histories in accordance with applicable laws, including the San Francisco Fair Chance Ordinance. We encourage candidates from all backgrounds to apply and join our mission to revolutionize healthcare through innovative AI solutions.