Design, deploy and monitor machine learning algorithms to extract and predict clinical findings from structured & unstructured data sources.
Requirements
- Must have a Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics or closely-related field
- 3 years of professional experience as a machine learning engineer performing software platform development
- Experience in end-to-end machine learning lifecycle within an Agile environment
- Developing and deploying machine learning models for NLP and computer vision
- Frameworks and libraries including PyTorch, TensorFlow, Scikit-Learn, Keras, Spacy, Hugging Face, and ML applications
- Applying statistical and ML techniques leveraging Python, including Pandas and Numpy
- Cloud computing and data analytics using AWS services (including S3, Athena, EC2, Lambda, SageMaker, CloudWatch, and Bedrock), along with SQL, Docker, and Linux for scalable processing
- Designing, building, and evaluating RAG-based Generative AI applications using LangChain, LlamaIndex or similar
Benefits
- Generous Paid Time Off
- 401k Matching
- Retirement Plan
- Four Day Work Week
- Generous Parental Leave
- Tuition Reimbursement
- Relocation Assistance