Posted:4 days ago|
Platform:
On-site
Full Time
Cozeva is a leading population health and value-based care platform that empowers payers, providers, and patients with data-driven insights. We are building the next generation of healthcare intelligence — integrating AI/ML, FHIR interoperability, and digital quality standards — to transform healthcare delivery and equity.
We are seeking a Senior Applied ML Engineer to bridge the gap between research and production. This role is for someone who understands both machine learning models and enterprise-scale software systems — ensuring Cozeva’s AI innovations are deployed, monitored, and scaled reliably within our SaaS platform.
You will work at the intersection of data science, AI, and software engineering, helping turn prototypes into high-performing, production-grade AI features that power value-based care.
● Model Integration & Deployment
○ Embed ML/AI models (LLMs, NLP, risk models, forecasting) into Cozeva’s software workflows and APIs.
○ Build production pipelines for training, evaluation, and deployment on cloud-native infrastructure.
● Scalable Systems Engineering
○ Design and maintain distributed data pipelines for claims, clinical, and EHR data.
○ Ensure performance, reliability, and cost efficiency of AI workloads (Aurora MySQL, Redshift, S3, EC2/K8s).
● MLOps Practices
○ Implement CI/CD for ML (model versioning, automated retraining, monitoring, rollback).
○ Monitor live model performance, drift, and fairness, ensuring compliance with Cozeva’s AI Governance Framework v1.1.
● Applied Problem Solving
○ Partner with AI Scientists to productionize models for:
■ NLP abstraction of clinical data (EHR notes, CCDs, FHIR).
■ Risk stratification and hospitalization/ED prediction.
■ Member engagement and HCC suspect modeling.
● Collaboration
○ Work closely with data engineers, SDEs, and product teams to deliver AI-driven features in Cozeva’s SaaS stack.
● Bachelor’s or Master’s in Computer Science, AI/ML, or related field.
● 5–8 years of experience in building and deploying ML models into production.
● Strong software engineering skills: Python, SQL, Docker/Kubernetes, distributed systems.
● Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face) and MLOps tools (MLflow, Kubeflow, SageMaker, or equivalent).
● Deep understanding of cloud infrastructure (AWS preferred: S3, EC2, RDS/Aurora, Redshift, IAM).
● Track record of delivering production-ready ML/AI features at scale.
● Experience with healthcare data (claims, EHR, FHIR, CCDs).
● Knowledge of value-based care, risk adjustment, or quality measurement.
● Experience designing responsible AI systems (bias detection, explainability, auditing).
● Contributions to open-source ML/MLOps projects.
● Mission with Impact: Improve health equity and outcomes for millions of patients.
● Hands-On AI: Deploy frontier models (LLMs, NLP, forecasting) directly into a SaaS platform.
● High Visibility: Collaborate closely with the CTO, scientists, and engineering leaders.
● Global Collaboration: Work with top-tier AI talent across the US and India.
● Culture of Service: Rooted in transparency, collaboration, and impact.
Cozeva
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