Note: The job is a remote job and is open to candidates in USA. NMDP is an organization with an AI Center of Excellence supporting cross-functional teams across the enterprise. The Senior AI/ML Engineer will design, develop, and deploy scalable machine learning, Generative AI, and Agentic AI solutions, while building cloud-based AI/ML pipelines and reusable frameworks. The role also partners with technical and business stakeholders, evaluates emerging AI technologies, and provides mentorship and support for AI adoption.
Responsibilities
- Design, develop, and deploy production-grade traditional ML models (e.g., regression, classification, clustering, recommender systems) for a variety of business use cases
- Design, build and operationalize Gen AI (such as Retrieval Augmented Generation) and emerging Agentic AI solutions to address domain specific needs, improve user experiences and automate business workflows
- 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)
- Integrate cloud-native and third-party AI SaaS solutions to accelerate delivery and reduce time to value
- Ensure AI/ML solutions are scalable, dependable, secure, and cost-effective within cloud environments
- Create reusable components, frameworks, and best practices to accelerate AI development
- Evaluating emerging AI technologies including GenAI and agentic AI (e.g., Model Context Protocol (MCP), Google’s Agent-to-Agent (A2A) protocol), as well as third-party low-code platforms) for their feasibility, scalability, and alignment with cross-functional business needs
- Solve for business problems by applying novel techniques and Innovating thinking
- The Senior AI/ML Engineer will partner with data scientists, architects, product managers, business stakeholders, and technical teams across the organization to ensure AI solutions align with organizational goals
- Providing direct technical support and mentorship to technical teams across the enterprise is essential for enabling successful AI/ML implementations
- Enabling other teams to adopt AI Into their products
- Leverage diverse skills and perspectives, leading to more effective problem-solving and decision-making
- Other duties as assigned
Skills
- Knowledge of machine learning algorithms, deep learning frameworks, Cloud AI technologies, GenAI technologies and emerging Agentic AI technologies
- Knowledge of cloud platforms (e.g., AWS, Azure, GCP) for scalable AI/ML development
- Knowledge of responsible AI principles, including bias mitigation and ethical deployment
- Knowledge of ML Ops best practices including CI/CD for ML, model monitoring, and versioning
- Proficient in Python and common ML/AI libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Strong understanding of data engineering, SQL, and feature engineering
- Direct 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)
- Ability to build robust, scalable, and efficient AI/ML solutions in cloud-native environments
- Ability to translate ambiguous business problems into clear, technical ML/AI tasks
- Ability to communicate complex ideas clearly to technical and non-technical stakeholders
- Ability to learn and adapt quickly to emerging AI technologies, techniques, and tools
- A bachelor's degree in computer science, information technology, engineering, or a related field is required. However, equivalent related experience and/or education may be considered as a substitute for the degree requirement upon evaluation
- 5+ years of experience designing and deploying ML/AI solutions in real-world environments
- Or a combination of 8 or more years of experience of software development/engineering, of which three or more years are AI/ML experience
- Proven experience with GenAI tools and technologies (e.g., LLMs, prompt engineering, Vector databases, RAG, fine-tuning)
- Master's or PhD 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
Benefits
- Remote work arrangement
- Regular, full-time employees are offered medical, dental, vision, life and disability, accident/critical illness/hospital, well-being, legal, identity theft and pet benefits.
- Retirement is offered to eligible employees.
- Paid time off and holidays are offered to eligible employees.
- Leave is offered to eligible employees.
- Incentive plans are offered to eligible employees.
Company Overview