Data Science | Machine Learning
Role details
Job location
Tech stack
Job description
Design advanced ML models across NLP, optimization, predictive modeling, and statistical learning. Own end to end MLOps pipelines data ingestion, training, deployment, monitoring, CICD. Collaborate with engineering, product, and domain teams to deliver production ready AI solutions. Drug Test: Yes -9 Panel
We are committed to fostering a diverse, inclusive, and equitable workplace where individuals from all backgrounds feel valued and empowered to contribute their unique perspectives. We strongly encourage applications from candidates of all genders, races, ethnicities, abilities, and experiences to join our team and help us build a culture of belonging.
Requirements
Must Have Skills Strong hands on experience with Core ML & Stats (optimization, supervised unsupervised learning) NLP (semantic search, embeddings, text modeling) MLOps (MLflow, Kubeflow, Airflow, Docker, CICD)
Nice to have skills Healthcare insurance Managed Care (MCO) experience familiarity with claims, clinical workflows, risk models, or regulatory frameworks is a strong plus. Experience with vector databases, hybrid semantic neural architectures, or agentic AI systems. Design advanced ML models across NLP, optimization, predictive modeling, and statistical learning. Own end to end MLOps pipelines data ingestion, training, deployment, monitoring, CICD. Collaborate with engineering, product, and domain teams to deliver production ready AI solutions. Build and scale Knowledge Graphdriven AI systems ontology design, graph embeddings, reasoning. Develop and fine tune LLMs for classification, summarization, RAG, and agentic workflows. Core ML Stats optimization, s
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