Note: The job is a remote job and is open to candidates in USA. Lifelancer is a talent-hiring platform in Life Sciences, Pharma and IT. They are seeking a Staff Machine Learning Engineer to design, build, and operationalize scalable Generative AI solutions across the affiliate line of business, working with various cloud technologies to enhance healthcare outcomes.
Responsibilities
- Drives the development and implementation of advanced machine learning models and algorithms to solve complex healthcare problems, leveraging techniques such as predictive modeling, deep learning, and natural language processing
- Collaborates with multiple departments, including data scientists, clinicians, and Information Technology (IT) professionals, to understand business requirements, define machine learning projects, and prioritize initiatives based on strategic objectives
- Interfaces with stakeholders to define performance metrics and evaluation methodologies for machine learning models, contributing to rigorous testing, validation, and performance monitoring of models to ensure accuracy and reliability
- Designs and implements scalable and efficient machine learning systems, including data pipelines, preprocessing, feature engineering, and model training, ensuring the quality and integrity of healthcare data used for analysis
- Advises on the optimization and improvement of data pipelines, model training processes, and infrastructure to enhance efficiency, scalability, and performance of machine learning solutions
- Consults on and presents technical findings, insights, and recommendations to both technical and non-technical stakeholders, contributing to the dissemination and application of machine learning insights in the healthcare industry
- Ensures compliance with data privacy regulations, ethical guidelines, and industry standards in machine learning engineering, supporting the development of protocols and practices for model interpretability, fairness, and transparency
- Manages team performance through regular, timely feedback as well as the formal performance review process to ensure delivery of exceptional services and engagement, motivation, and team development
- Stays up-to-date with the latest advancements in machine learning and related technologies, continuously exploring and evaluating new algorithms and methodologies to enhance machine learning capabilities in healthcare applications
- Design, build, and deploy production-grade LLM and GenAI applications using the full breadth of AWS Bedrock and GCP Vertex AI capabilities (models, tuning, pipelines, vector search, guardrails, evaluation)
- Build cloud-native AI systems using: Serverless architectures (AWS Lambda, Step Functions, EventBridge; Cloud Functions, Cloud Run); Event-driven architectures (SNS/SQS, Pub/Sub, EventBridge, triggers); Microservices and APIs (Node.js, Java, Python)
- Architect agentic AI systems using Bedrock Agents, Vertex AI Agent Builder, or approved frameworks (LangGraph, LangChain, LlamaIndex Agents)
- Deliver multi-step reasoning, tool-use, and workflow orchestration for enterprise use cases
- Comfortable designing and developing AI Agents using Copilot Studio and Cloud flow (Power Automate)
- Develop robust Retrieval-Augmented Generation (RAG) systems using Bedrock Knowledge Bases, Vertex AI Vector Search, or custom vector databases (OpenSearch, Pinecone, FAISS, pgvector)
- Design document ingestion, embedding, chunking, grounding, and retrieval pipelines that integrate securely with enterprise data
- Lead model experimentation, fine‑tuning, evaluation, deployment, and monitoring across cloud platforms
- Optimize cost, performance, token usage, latency, and scaling for production workloads
- Ensure all solutions meet CVS Health’s Responsible AI standards, including model documentation, governance, risk assessment, and auditability
- Design systems that adhere to HIPAA, data privacy, and security requirements
- Partner with product, engineering, data, security, and compliance teams to shape roadmaps and solution direction
- Mentor engineers and contribute reusable patterns, frameworks, and platform accelerators
Skills
- 8+ years in large-scale software development
- 5+ years solution architecture or system design experience
- 5+ years building large-scale microservices/APIs using Node.js
- 3+ years hands‑on experience with GCP and AWS (serverless, event-driven, AI/ML, CI/CD)
- AWS Bedrock (any combination of models, agents, knowledge bases, guardrails, tuning, evaluation) or GCP Vertex AI (Model Garden, Extensions/Agents, Vector Search, Pipelines, Tuning) or similar technologies
- Strong communication and leadership skills
- Strong experience with Python for AI/ML engineering
- Production experience with: Agentic AI frameworks, RAG architectures and vector databases, Serverless and event-driven designs
- Experience with Vertex AI's Generative AI Studio, vector search orchestration, and agent capabilities
- Hands-on experience with vector databases (OpenSearch, Pinecone, FAISS, pgvector, Milvus)
- Strong knowledge of prompt engineering, evaluation, observability, and LLM security patterns
- Ability to write clear design docs, architectural diagrams, runbooks, and technical briefs
- Agile/SAFe experience in large enterprises
- Cloud certifications (AWS/GCP) preferred
Benefits
- CVS Health bonus, commission or short-term incentive program
- Award target in the company’s equity award program
- Medical, dental, and vision coverage
- Paid time off
- Retirement savings options
- Wellness programs
- Other resources, based on eligibility
Company Overview