AI/ML Engineer

NMDP is seeking an AI/ML Engineer to play a crucial role in the AI Center of Excellence, supporting cross-functional teams. The role involves designing and developing machine learning and artificial intelligence solutions to improve user experiences and automate business workflows.

Responsibilities:

• Work across diverse GenAI platforms like AWS, Salesforce, Oracle, Snowflake, MS Copilot, and other 3rd party GenAI platforms and libraries
• Automate workflows involving extraction of complex, multimodal unstructured content from variety of sources in to highly accurate and reliable structured content using platforms like AWS Textract and Bedrock
• Design and build MCP hosts, clients and servers
• Establish and use frameworks for automated LLM testing
• Create regression test suites to detect drift or prompt breakage
• Integrate with internal and external web services using secure authentication and authorization mechanisms
• Adopt and ensure safe practices to protect against prompt injections, jailbreaks, and conform to enterprise security guidelines
• Design, develop, and deploy production-grade traditional ML models (e.g., regression, classification, clustering, recommender systems) for a variety of business use cases
• Design, maintain, and optimize end-to-end AI/ML pipelines including data ingestion, training, evaluation, deployment, and monitoring on cloud infrastructure (e.g., AWS or equivalent)
• Ensure AI/ML solutions are scalable, reliable, secure, and cost-effective within cloud environments
• Create reusable components, frameworks, and best practices to accelerate AI development
• Design and develop GenAI solutions using prompt engineering, Context Engineering, Retrieval-Augmented Generation (RAG), and custom pipelines
• Design and develop interoperable AI agents using Model Context Protocol (MCP) and/or Google A2A
• Partner with data scientists, architects, product managers, business stakeholders and technical teams across organization to align AI solutions with organizational goals
• Provide hands-on technical support and mentorship to technical teams across the enterprise

Requirements:

• Machine learning algorithms, deep learning frameworks, Cloud AI technologies, GenAI technologies and emerging Agentic AI technologies
• Cloud platforms (e.g., AWS, Azure, GCP) for scalable AI/ML development
• Responsible AI principles, including bias mitigation and ethical deployment
• ML Ops best practices including CI/CD for ML, model monitoring, and versioning
• Build robust, scalable, and efficient AI/ML solutions in cloud-native environments
• Translate ambiguous business problems into clear, technical ML/AI tasks
• Communicate complex ideas clearly to technical and non-technical stakeholders
• Learn and adapt quickly to emerging AI technologies, techniques, and tools
• Bachelor's degree in computer science, Engineering, or related field
• 3+ years of experience designing and deploying ML/AI solutions in real-world environments in which time candidates will have created strong proficiency with the following:
• Very strong Python skills with strong hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Gemini, Anthropic, etc.) using Python and Python based frameworks
• Strong hands-on experience in prompt engineering, context construction, grounding strategies
• Strong hands-on experience with Retrieval Augmented Generation (RAG) extracting, chunking and create embeddings from unstructured documents from diverse sources including O365(email, word, excel), PDFs, and webpages
• Comfortable building Model Context Protocol (MCP) clients, servers and hosts
• Strong Expertise in building REST APIs and integrating with internal/external APIs
• Hands-on experience with Intelligent Document Processing and/or OCR technologies on complex documents
• Knowledge of Google A2A
• Deep experience in AWS (Lambda, Bedrock, Step Functions, API Gateway, IAM)
• Strong experience with Observability tools like Dynatrace, or other similar GenAI observability tools
• Excellent GenAI foundations and concepts
• Clear understanding of enterprise data privacy, AI governance, and observability
• Proficiency in Python and common ML/AI libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Strong understanding of data engineering, SQL, and feature engineering
• Hands-on experience with cloud services such as AWS Sagemaker, Lambda, ECS, S3, and IAM
• Familiarity with containerization (Docker) and orchestration (e.g., Airflow, Kubeflow)
• Working with version control and collaboration tools (Git, Jira, Confluence etc)
• Master's in a related technical field
• Hands-on experience with agentic AI frameworks
• Prior contributions to open-source AI/ML projects or published research
• AI/ML certifications from cloud providers
• Experience in highly regulated industries (e.g., healthcare, finance) a plus