Machine Learning Engineer l

4 weeks ago

Dallas, United States Cohere Health Full time

We are looking for a Machine Learning Engineer l and Machine Learning Engineer ll to join our team Our ML team’s work is focused on designing, deploying, and monitoring production models which extract or predict relevant clinical findings from structured and unstructured data sources. In this role, you’ll join our growing team of world-class engineers, statisticians, and clinical experts to deploy machine learning algorithms that help automate burdensome administrative clinical practices. You will be tasked with finding the most promising opportunities for impact and then delivering on them. This is a unique opportunity to join a high caliber engineering team that is growing quickly. You will build impactful healthcare technology on a modern tech stack. What you’ll do: • Perform in-depth analysis of healthcare data to independently design, develop, and deliver clinical ML models. • Build reliable and scalable production machine learning systems • Work on feature engineering, statistical analysis, developing novel ML techniques, understanding performance, and improving model run time. • Work cross-functionally across diverse stakeholders, including product managers, statisticians, clinicians, and clinical analysts. What you’ll need: • You have 1-4 years full time professional experience in ML • You have an MS in computer science, machine learning, computational linguistics, statistics, mathematics or similar field • You have hands on experience building with modern language models, including context-engineering LLMs or fine-tuning SLMs • You understand scientific best practice in experimental design and can independently perform data collection, measurement, and interpretation of results • You have experience configuring, training, evaluating, deploying, and maintaining models in a production setting • Advanced proficiency in Python and familiarity with ML frameworks such as PyTorch. Bonus points for: • Experience with healthcare data such as claims and EMR data • Knowledge of NCQA HEDIS guidelines and CMS STARS specifications • Experience extracting unstructured clinical data concepts from clinical data (such as EMR or Utilization Management data) • Experience with OCR • Experience with graph databases or network analysis • Hands on experience using AWS tools such as SageMaker Studio and Neptune

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