AI Machine Learning Engineer

Role overview

Responsibilities

• check_circle Designs, builds, and maintains robust data pipelines to collect, clean, and transform data from various sources used in analysis, modeling, and deployed operational environments
• check_circle Develops and implements ML models and algorithms to solve complex business problems and improve decision-making processes across the full life cycle, including problem framing, data collection, data preparation, feature engineering, model selection, training, evaluation, deployment, retraining, and advancement
• check_circle Designs and builds AI agents that execute in workflows within enterprise systems (databases, CRMs, ticketing, knowledge bases) and that are deployed with reliable/safety guardrails
• check_circle Implements end-to-end agent orchestration (prompting, memory/state, tool-calling, retries/fallbacks) and develops evaluation frameworks (test suites, simulations, human-in-the-loop review) to improve accuracy and reduce error
• check_circle Designs, builds, and maintains Retrieval-Augmented Generation (RAG) GPT applications by integrating enterprise knowledge sources (documents/databases) with embeddings, vector search, and prompt orchestration to deliver accurate, grounded responses with evaluation and safety guardrails
• check_circle Analyzes large datasets to uncover trends, patterns, and insights, and creates visualizations and reports to communicate findings to stakeholders
• check_circle Monitors and evaluates the performance of data models and systems, and makes necessary adjustments to optimize accuracy and efficiency
• check_circle Documents processes, methodologies, and model development to ensure transparency and reproducibility
• check_circle Provides training and support to other team members or departments on data tools, techniques, and best practices
• check_circle Consults with internal IT teams to ensure infrastructure supports stable, well-designed, highly available, and well-maintained Data Science and AI applications
• check_circle Stays current with emerging technologies and industry trends to continuously improve data engineering practices and contributes to the development of cutting-edge solutions
• check_circle Ensures the accuracy, consistency, and security of data; implements and enforces data governance policies and best practices.

Basic qualifications

• Bachelor’s degree in Computer Science, Analytics, or related field from an accredited college or university. Masters of Science degree preferred.
• Five (5) or more years of experience in data engineering, data science, or a related role, with hands-on experience in building and deploying machine learning models.