Senior Applied AI Engineer

Join Omada Health, a digital care provider focused on empowering individuals to achieve their health goals through sustainable behavioral change. As a Senior Applied AI Engineer, you will lead the deployment of sophisticated AI models and applications, driving business outcomes and making a meaningful impact in the healthcare industry. This remote-first position offers flexible vacation, wellness days, parental leave, and resources to thrive.

• Lead the creation and deployment of AI solutions, particularly focusing on leveraging the power of large language models (LLMs) to influence business outcomes.
• Collaborate with cross-functional teams to iterate on ideas, solve problems, and achieve shared goals, ensuring that deployed models operate at peak efficiency.
• Monitor model performance post-deployment, making iterative improvements based on data-driven insights, and linking AI solutions to tangible business impacts.

• Familiarity with Agile methodologies, demonstrating effectiveness in a fast-paced, iterative development environment
• General experience in cloud ML platforms (AWS, Azure, GCP), especially with their ML services (Sagemaker and Azure ML)
• BA/BS in Computer Science or a related technical field or equivalent practical experience
• 5+ years of experience deploying AI models with demonstrated business impact
• Deep Expertise in utilizing tools for Generative AI interaction (OpenAI, Bedrock, Huggingface TGI, Ollama, langchain, llamaindex)
• Expertise in machine learning tools (e.g., AWS SageMaker, PyTorch, Hugging Face)
• Proven track record of designing, deploying, and managing end-to-end AI solutions, with a particular emphasis on Generative AI, prompt engineering techniques, and fine tuning
• A lifelong learner, continuously seeking to stay updated on new technologies and methodologies in the fast-evolving AI landscape
• Strong capability for cross-team collaboration, working seamlessly with stakeholders across functional areas to deploy AI solutions that meet broader business needs
• A natural problem-solver, comfortable with navigating ambiguity and making decisions in complex environments
• Interest in the intersection of healthcare and AI
• Successful monitoring of model performance post-deployment, with an ability to link AI solutions to tangible business impacts