The company is looking to develop, deploy, and scale AI capabilities across its platform to improve patient outcomes and drive its mission forward.
Requirements
- Advanced proficiency in Python and core machine learning libraries (TensorFlow, PyTorch, Scikit-learn, etc.).
- Deep understanding of applied ML techniques including NLP, classification, prediction, and time-series analysis.
- Hands-on experience working with Generative AI models (e.g. GPT, LLaMA, Claude), including prompt engineering, fine-tuning, and integrating GenAI into production applications.
- Strong grasp of MLOps principles and tools for model lifecycle management (e.g., MLflow, SageMaker, Vertex AI).
- Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
- Solid grounding in algorithms, data structures, and applied mathematics.
- Experience with healthcare, real-world data (e.g., claims, EMR), or regulated environments (e.g., HIPAA compliance) is preferred.
Responsibilities
- Define and refine AI engineering strategy in alignment with business goals and product opportunities.
- Design and guide the implementation of end-to-end AI/ML pipelines, including data ingestion, model training, deployment, and monitoring.
- Own the architecture and scalability of deployed AI models in cloud environments.
- Implement monitoring and retraining workflows to ensure long-term reliability and performance of AI solutions.
- Contribute to infrastructure decisions related to model training environments, deployment tools, and experimentation platforms.
- Translate business needs into actionable technical approaches that consider data availability, ethical implications, and operational constraints.
- Communicate clearly with both technical and non-technical stakeholders to ensure alignment and transparency.
Other
- Lead, mentor, and support a team of AI engineers, including direct supervision of junior AI engineers.
- Establish engineering best practices for AI development, including coding standards, peer reviews, and model governance.
- Foster a collaborative, feedback-driven team culture rooted in company values: integrity, grit, collaboration, and adaptability.
- Demonstrated ability to communicate technical concepts clearly across audiences.
- Strong sense of ownership and accountability in both individual and team contributions.
- Passion for growing talent and building an inclusive, learning-focused team culture.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. PhD is a plus.
- 6+ years of experience working in AI/ML roles, with 2+ years of experience in a technical leadership position.
