Senior Machine Learning Engineer

Cohere Health

12h • Remote

About The Position

Cohere Health, Inc. is seeking a Senior Machine Learning Engineer to design, deploy, and monitor machine learning algorithms for extracting and predicting clinical findings from structured and unstructured data. This role involves evaluating state-of-the-art deep learning approaches, writing and maintaining reusable codebases for the ML lifecycle, building and monitoring production ML systems, and collaborating with cross-functional teams. The engineer will develop multi-modal document understanding systems and provide guidance and mentorship to junior engineers and interns.

Requirements

• 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.
• 3 years of experience in the end-to-end machine learning lifecycle within an Agile environment.
• Developing and deploying machine learning models for NLP and computer vision, implementing architectures such as Transformer-based models, and CNN-based models.
• Experience with 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.
• Experience with 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 while managing workflows with JIRA, Confluence, and Git.

Responsibilities

• Design, deploy and monitor machine learning algorithms to extract and predict clinical findings from structured & unstructured data sources.
• Evaluate state-of-the-art deep learning approaches (e.g. transformers) for embedding, retrieval, classification and generative use cases.
• Write and maintain reusable codebases to perform data preprocessing, model training, evaluation, and deployment.
• Build, deploy and monitor reliable and scalable production machine learning systems.
• Work cross-functionally with diverse stakeholders including product managers, clinicians, and technical leadership.
• Develop multi-modal document understanding systems for information extraction, incorporating segmentation, ordering, and classification to enrich metadata for improved retrieval and generation workflows.
• Provide software and machine learning best practice guidance to junior engineers.
• Provide onboarding support and mentorship to interns.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior