Senior Machine Learning Engineer, Infrastructure
Job Description
Rad AI is seeking an experienced Senior Machine Learning Engineer to join their team. The ideal candidate will have expertise in maturing, scaling, and optimizing the infrastructure of a quickly growing product, and a passion for building, teaching, learning, and collaborating in a high-performing cross-functional team.
Rad AI has raised $80+ million to date and has formed a partnership with Google to collaborate on the future of generative AI in healthcare. They are recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie. Currently, more than 1/3 of radiology groups and healthcare systems, including Kaiser Permanente, HCA Healthcare, and Geisinger, leverage Rad AI's Gen AI advancements.
The role involves designing, implementing, and maintaining the infrastructure that supports machine learning applications, services, and workflows. The candidate will be responsible for building and improving the ML platform, leveraging low-level programming languages, cloud native services, and serverless architectures to build scalable and resilient systems.
Key responsibilities include:
- Leading the design and implementation of infrastructure projects
- Developing and implementing automation tools for model training and deployment
- Investigating and optimizing the existing pipeline
- Balancing metrics and alerting with cost efficiency
The ideal candidate should have:
- 4+ years of experience in ML Systems Engineering
- Strong experience with infrastructure and DevOps tools
- Experience in distributed systems, storage systems, and databases
- Strong knowledge of cloud computing platforms, especially AWS
- Experience with infrastructure-as-code tools and monitoring systems
Rad AI offers comprehensive benefits, including medical insurance, 401(k), flexible PTO, and a remote-first work environment. They value diversity and provide equal employment opportunities to all employees and applicants.
Join Rad AI's world-class team in building and deploying AI solutions that will make a difference in millions of people's lives while working in a mission-driven, transparent, and collaborative environment.
Responsibilities For Senior Machine Learning Engineer, Infrastructure
- Design, implement, and maintain the infrastructure that supports our machine learning applications, services, and workflows
- Build, maintain, and improve our ML platform that supports continuous integration, continuous delivery, and continuous training for our machine learning models
- Leverage low-level programming languages, cloud native services, and serverless architectures to build scalable and resilient systems
- Plan, design and develop components in the data pipeline to enable various machine learning models in production
- Lead the design and implementation of infrastructure projects, including the development of technical designs, plans, and specifications, along with their evolutions and updates
- Design, deploy, and maintain the full ML platform stack including capabilities such as monitoring and data observability, the full model lifecycle, etc.
- Investigate the existing pipeline, identify bottlenecks and optimize the throughput and latency of ML components
- Balance metrics and alerting with cost efficiency and detail
- Develop and implement automation tools for model training and deployment
Requirements For Senior Machine Learning Engineer, Infrastructure
- 4+ years of experience in ML Systems Engineering
- 4+ years of industry experience writing in Python (preferable) or other common languages in the ML domain
- Strong experience with infrastructure and DevOps tools such as Kubernetes, Docker, and Ansible
- Experience in distributed systems, storage systems, and databases
- Strong knowledge of cloud computing platforms such as AWS (preferable), GCP, and Azure
- Experience with infrastructure-as-code tools such as Terraform (preferable), Pulumi, Cloud Formation, etc.
- Experience with monitoring, tracing, and logging tools such Cloudwatch, NewRelic, Prometheus, etc.
- Excellent communication skills, with a strong sense of ownership and a systematic approach to problem-solving
- Proven ability to manage and lead active incidents, address what caused them, and establish systems to avoid them in the future via blameless postmortems
Benefits For Senior Machine Learning Engineer, Infrastructure
- Comprehensive Medical, Dental, Vision & Life insurance
- HSA (with employer match), FSA, & DCFSA
- 401(k)
- 11 paid company holidays
- Location-flexibility (remote-first company!)
- Flexible PTO policy
- Annual company-wide offsite
- Periodic team offsites
- Annual equipment stipend
- Equity
