LLMOps + MLOps - Senior Associate

Role & responsibilities

• Developing and deploying LLMOps and MLOps workflows that support model training, testing, deployment, and monitoring across client solutions
• Translating advanced data science and machine learning requirements into scalable automation, orchestration, and lifecycle management approaches
• Applying statistical analysis, predictive modeling, and data engineering techniques to improve model performance and operational reliability
• Supporting client engagements by gathering technical requirements, interpreting feedback, and shaping practical implementation plans
• Building data pipelines and data quality controls that support machine learning use cases and AI-enabled solutions
• Evaluating model behavior, retraining needs, and drift signals by using monitoring tools and analytical methods
• Documenting technical decisions, solution design, and deployment steps to support transparency and reuse across project workstreams
• Mentoring junior team members on machine learning workflows, AI tooling, and delivery methods while contributing to team development

What Sets You Apart

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Demonstrating LLMOps and MLOps delivery across client engagements
• Utilizing AI tooling, data pipelines, and model monitoring
• Interpreting data to guide recommendations and delivery priorities
• Building client connections while navigating ambiguity and change
• Mentoring junior team members through complex technical work