Senior ML/AI Engineer

Equip is the leading virtual, evidence-based eating disorder treatment program on a mission to ensure that everyone with an eating disorder can access treatment that works. The Senior Machine Learning/AI Engineer will be responsible for designing, building, evaluating, and refining data-driven products using ML and AI solutions to create a positive impact across various business domains.

Responsibilities:

• Architect and lead end-to-end ML/AI pipelines — including training, fine-tuning, experimentation, and deployment — setting technical standards across the team
• Design and own CI/CD pipelines for ML/AI workflows, including automated testing, model versioning, and continuous delivery to production environments
• Build and maintain scalable ML/AI infrastructure on cloud platforms
• Develop monitoring and observability frameworks to track model performance, data drift, and system health in production
• Develop tools and processes that leverage ML/AI to enhance user experience, extract insights from large datasets, and increase operational efficiency
• Research state-of-the-art ML/AI advancements and translate them into production-ready systems
• Design, build, and maintain APIs for exposing ML/AI models and data services to internal and external consumers
• Mentor junior and mid-level data scientists and engineers, conducting code reviews and driving engineering best practices across the ML organization
• Collaborate with cross-functional stakeholders to scope, prioritize, and deliver high-impact ML/AI solutions
• Perform other duties as assigned

Requirements:

• Bachelor's or master's degree in Computer Science, Statistics, Mathematics, Operations Research, Engineering, or a related quantitative field
• 5+ years of demonstrated experience developing, training, evaluating, deploying, monitoring, and iterating on production-level ML/AI models and pipelines at scale
• Solid knowledge of mathematics and statistics underpinning ML methods and model evaluation
• Experience with large language models (e.g., OpenAI) and applied NLP on unstructured text data, including fine-tuning and deployment of LLM-based systems
• Strong programming skills in Python, Python-based ML frameworks, and SQL
• Deep understanding of MLOps principles: deployment, model versioning, experiment tracking, automated retraining, and production observability
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and ML platform tooling (e.g., SageMaker, MLflow, Kubeflow)
• Experience designing, building, and consuming APIs, including best practices around versioning, authentication, and performance at scale
• Solid foundation in software engineering principles — writing clean, maintainable, testable, and well-documented code
• Proficiency with Git/GitHub, including branching strategies and code review workflows
• Demonstrated ability to lead technical projects, influence architectural decisions, and communicate effectively with diverse, cross-functional teams
• Comfortable driving results in a fast-paced, rapidly evolving environment