Participate in end-to-end AI/ML projects, from research and design through deployment and ongoing maintenance, to deliver scalable production systems.
Implement ML pipelines and production-grade infrastructure that support high-volume workloads and reliable model execution.
Partner with cross-functional teams to integrate AI capabilities that align with business goals and customer needs.
Research and prototype new AI/ML algorithms and techniques to support innovation and product development.
Help establish best practices for AI/ML development, deployment, monitoring, and governance across the team.
Monitor model performance, scalability, and cost in production and contribute to continuous optimization.
Apply AI tools and techniques in day-to-day engineering work to improve productivity, support experimentation, and strengthen evaluation of model behavior, outputs, and system impact.
Advocate for responsible AI by considering fairness, transparency, data privacy, and appropriate use in model design and deployment.
Collaborate with engineering partners to move models from prototype to production using repeatable, maintainable approaches.
Document technical decisions, model behavior, and operational considerations to support shared understanding and long-term maintainability.

Bachelor’s Degree in Data Science, Mathematics, Statistics, Operations Research, Computer Science/Engineering, or a related technical field
4–6 years of professional experience in software engineering, with exposure to software development, data science, or AI/ML work.
Experience contributing to AI/ML projects across the model lifecycle, including research, prototyping, deployment, or monitoring.
Foundational knowledge of classical AI/ML algorithms, deep learning, Natural Language Understanding and Processing, and Generative AI concepts.
Familiarity with large language models, GPT, BERT, LangChain, and LangGraph concepts and applications.
Experience or exposure to building and deploying AI/ML systems in AWS.
Proficiency in Python and working knowledge of a JVM language/service.
Proficiency in working with SQL and non-SQL data.
Experience with at least one major ML framework, such as TensorFlow or PyTorch.
Exposure to MLOps and machine learning workflow orchestration; experience with AWS SageMaker is a plus.

Senior AI/ML Engineer

Key skills