AI/ML Developer – Healthcare - Remote - NO GC/USA

[Adarsh mallik]

Job Title: AI/ML Developer – Healthcare
Location: USA – Remote
Duration: Contract / Contract-to-Hire 

Role Summary
We are seeking an AI/ML Developer with healthcare domain experience to build, deploy, and optimize machine learning solutions that support clinical, operational, claims, and population health use cases. This role will partner with data engineering, product, and stakeholders to deliver production-grade ML pipelines, APIs, and MLOps workflows in a secure, compliant environment.

Key Responsibilities

• Develop and productionize ML models for healthcare use cases (risk prediction, readmission, claims analytics, utilization, NLP on clinical notes, etc.).

• Build end-to-end ML pipelines: data preparation, feature engineering, training, validation, and monitoring.

• Implement model serving via REST/gRPC APIs and integrate with downstream applications.

• Apply best practices for evaluation, bias testing, explainability, and reproducibility.

• Create and maintain MLOps workflows (CI/CD, model registry, monitoring, drift detection, automated retraining).

• Optimize model performance and cost; profile code and improve inference latency.

• Collaborate with data engineers on scalable datasets and reliable data pipelines.

• Write clean documentation, tests, and technical design artifacts.

• Follow security and compliance controls aligned with healthcare standards (HIPAA).

Required Skills

• 4+ years of hands-on ML development experience (or strong equivalent project delivery).

• Strong Python and ML libraries: scikit-learn, PyTorch or TensorFlow; strong SQL.

• Experience with NLP (preferred): transformers, embeddings, information extraction, classification.

• Experience deploying models to production (Docker/Kubernetes preferred) and building APIs (FastAPI/Flask).

• Experience with MLOps tooling: MLflow, model registry, CI/CD pipelines, monitoring (Prometheus/Grafana or equivalent).

• Cloud experience (any): AWS / Azure / GCP (storage, compute, IAM, networking basics).

• Healthcare data familiarity: EHR/EMR, claims, labs, ICD-10/CPT, HL7/FHIR (any exposure helps).

• Strong communication and ability to work with both technical and non-technical stakeholders.

Preferred / Nice to Have

• Experience with Spark/Databricks for large-scale training.

• Experience with LLM-based pipelines (RAG, prompt orchestration, evaluation frameworks) in regulated settings.

• Knowledge of PHI handling, de-identification, audit logging, and access control patterns.

• Experience with feature stores (Feast or equivalent).