Machine Learning Engineer, Flo Health

• 4+ years of professional experience in the field of machine learning
• Demonstrated success in building and deploying large-scale machine learning models; experience with large-scale LLM applications is a bonus
• Ability to devise creative solutions to intricate technical challenges, including experience in systems design with the ability to architect and explain ML/LLM pipelines
• Strong Python programming skills for efficient model development and deployment
• Experience with both traditional ML and modern LLM frameworks
• Understanding of the entire ML/LLM development process, including CI/CD, version control, testing, MLOps/LLMOps, and agile methodologies
• Experience in building and managing data pipelines using tools like Apache Spark
• Excellent communication skills and ability to collaborate with diverse teams
• Commitment to responsible AI practices, including fairness, accountability, and transparency

Desirable

• You will be developing groundbreaking features that leverage our medical expertise, technical skills, rapid adoption of new technologies (like LLMs), product knowledge, and a deep understanding of our users’ needs.
• If you’re passionate about technology, especially advancements in generative AI, and driven by delivering value to users, we would love to hear from you!
• Explore, develop and test complex ML/AI systems to improve female health
• Work with state-of-the-art technologies, such as most advanced LLMs and Generative AI approaches, to build solutions that are medically safe and work at scale
• Work in a fast-paced environment to quickly build and validate product hypotheses, taking end-to-end ownership of ML/AI products
• Build the future-proof infrastructure for serving Gen AI features at Flo, bringing our AI vision and strategy to life
• Constantly improve our technical capabilities by researching and implementing best practices in the context of the fastly evolving space of LLMs
• Work in a cross-functional setup alongside other engineering (ML, Backend, QA), product, and analytics teams