Equip Health - Senior ML/AI Engineer
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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.
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.
Benefits
• Flex PTO policy (3-5 wks/year recommended) + 11 paid company holidays. • Competitive Medical, Dental, Vision, Life, and AD&D insurance. • Equip pays for a significant percentage of benefits premiums for individuals and families. • Maven, a company paid reproductive and family care benefit for all employees. • Employee Assistance Program (EAP), a company paid resource for mental health, legal services, financial support, and more! • $50/month stipend added directly to an employee’s paycheck to cover home internet expenses. • One-time work from home stipend of up to $500. • Physical Demands • Work is performed 100% from home with limited travel for team meetings. This is a stationary position that requires the ability to operate standard office equipment and keyboards as well as to talk or hear by telephone. Sit or stand as needed. • At Equip, Diversity, Equity, Inclusion and Belonging (DEIB) are woven into everything we do. At the heart of Equip’s mission is a relentless dedication to making sure that everyone with an eating disorder has access to care that works regardless of race, gender, sexuality, ability, weight, socio-economic status, and any marginalized identity. We also strive toward our providers and corporate team reflecting that same dedication both in bringing in and retaining talented employees from all backgrounds and identities. We have an Equip DEIB council, Equip For All; also referred to as EFA. EFA at Equip aims to be a space driven by mutual respect, and thoughtful, effective communication strategy - enabling full participation of members who identify as marginalized or under-represented and allies, amplifying diverse voices, creating opportunities for advocacy and contributing to the advancement of diversity, equity, inclusion, and belonging at Equip.
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