[Remote] Senior Machine Learning Engineer
Note: The job is a remote job and is open to candidates in USA. Cohere Health is a company focused on leveraging machine learning in healthcare, and they are seeking a Senior Machine Learning Engineer to design and deploy algorithms for clinical findings extraction. The role involves working with diverse stakeholders and developing scalable machine learning systems while providing guidance to junior engineers.
Responsibilities
- 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
Skills
- 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 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
- Cloud computing and data analytics using AWS services (including S3, Athena, EC2, Lambda, SageMaker, CloudWatch, and Bedrock)
- Experience with SQL, Docker, and Linux for scalable processing
- Designing, building, and evaluating RAG-based Generative AI applications using LangChain, LlamaIndex or similar
- Managing workflows with JIRA, Confluence, and Git
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