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