Job Specifications
About Us
We're continuing to build a transformative healthcare accreditation platform that is revolutionizing how our clients and new hospitals manage compliance, quality improvement, and regulatory processes. Our platform combines cutting-edge technology with deep healthcare domain expertise to solve real problems for healthcare organizations nationwide.
The Opportunity
The goal is to have interns turn into full time employees; Therefore, you will be given full time responsibilities day one. To add onto that, you will be working in a high velocity growth startup and will be required to move fast. You'll work directly with our engineering team on a production healthcare platform, gaining hands-on experience with enterprise-grade systems while making real contributions that impact our product and customers.
Compensation Structure
Base position is unpaid, however qualified candidates may receive upfront equity compensation based on their experience level and demonstrated capabilities. We evaluate each applicant individually and offer equity packages commensurate with their potential contribution.
About the Role
We're hiring for an AI/ML Developer. This role encompasses Machine Learning with Data Science and AI/ML Development. To be considered, you must have a deep expertise in a focus and some knowledge of the latter.
Requirements:
Deep specialization in either (SageMaker/Azure ML + statistics) or (Python + FastAPI + AWS + RAG)
Strong understanding of modern practices and version control (Git)
Ability to work collaboratively within a specialized team structure
Passion for building production-ready, scalable systems
Nice to Have:
Experience working in team environments with separated responsibilities
Understanding of both statistical modeling and production AI deployment
Previous experience with healthcare or regulated industries
What You'll Build
ML & Data Science:
Predictive analytics: Time-series models, classification systems, and risk assessment frameworks
Statistical analysis: Hypothesis testing, A/B testing, and experimental design
Feature engineering: Domain-specific feature stores and automated transformation pipelines
ML pipelines: End-to-end workflows/feature engineering using AWS SageMaker or Azure Machine Learning
Data visualizations: Interactive dashboards using Plotly, Tableau, and custom solutions
AI/ML Development:
RAG systems: Retrieval-augmented generation for domain-specific knowledge bases using Bedrock and Bedrock Agents
Python FastAPI servers: Production AI inference endpoints and services
AWS AI services: Lambda-based inference, Bedrock integration, vector database management
Semantic search: Knowledge extraction and contextual Q&A systems using ChromaDB, FAISS, S3 Vectors, and OpenSearch(Hybrid search)
Key Responsibilities
Conduct exploratory data analysis to identify patterns in complex healthcare datasets
Perform statistical analysis and hypothesis testing on business metrics and KPIs
Design and execute A/B tests for model performance evaluation
Build and deploy ML models using AWS SageMaker or Azure Machine Learning
Develop automated feature engineering and data transformation pipelines
Create comprehensive visualizations and reporting systems
Train classification, regression, and forecasting models
Implement MLOps practices for model versioning and monitoring
Build practical Agents and RAG systems using AWS Bedrock, Bedrock Agents, and vector databases
Manage vector databases: ChromaDB, FAISS, S3 Vectors, and OpenSearch
Develop document processing pipelines for text extraction and analysis
Create production Python FastAPI servers for real-time AI inference
Implement semantic search and knowledge extraction from document repositories
Design Lambda-based inference systems on AWS
Integrate LLMs for domain-specific chatbots and Q&A systems
Develop ETL processes for external data sources and APIs
Required Qualifications
Candidates must meet all Core Qualifications.
Core Qualifications:
Advanced Python programming skills (2+ years)
Git for version control
Understanding of deployment and production systems
Collaborative development workflows
ML & Data Science:
2+ years with Python ML libraries (scikit-learn, pandas, numpy, scipy)
1+ years with AWS SageMaker or Azure Machine Learning
Strong statistical analysis skills (hypothesis testing, A/B testing, experimental design)
Data visualization expertise (matplotlib, seaborn, plotly, Tableau)
SQL proficiency for analytics and data querying
MLflow for experiment tracking
AI/ML Development:
Strong FastAPI experience for building production AI servers
1+ years with AWS services (Lambda, Bedrock, Bedrock Agents, S3, EC2)
RAG development experience with vector databases (ChromaDB, FAISS, S3 Vectors, OpenSearch)
NLP/Document processing expertise (text extraction, classification, information retrieval)
Nice to Have:
Healthcare or regulated industry experience
Experience with Hugging Face transformers and LLMs
Time-series f