Salary Range: 140000 to 165000 (Currency: USD) (Pay period: per-year-salary)
About Equip
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. Created by clinical experts in the field and people with lived experience, Equip builds upon evidence-based treatments to empower individuals to reach lasting recovery. All Equip patients receive a dedicated care team, including a therapist, dietitian, physician, and peer and family mentor. The company operates in all 50 states and is partnered with most major health insurance plans. Learn more about our strong outcomes and treatment approach at www.equip.health
Founded in 2019, Equip has been a fully virtual company since its inception and is proud of the highly-engaged, passionate, and diverse Equisters that have created Equip’s culture. Recognized by Time as one of the most influential companies of 2023, along with awards from Linkedin and Lattice, we are grateful to Equipsters for building a sustainable treatment program that has served thousands of patients and families.
About the role
The Machine Learning (ML) Engineer II will be responsible for designing, building, evaluating, productizing, and refining data-driven products and insights using ML and AI solutions (e.g. large language models). This role will implement ML/AI models to solve complex projects and create a positive impact across all our business domains, including Product, Clinical Operations, Commercial, and more. The ML Engineer II is an analytical thinker, effective communicator and collaborator, is detail oriented, and works comfortably in fast-paced environments. As part of the Data and Insights team, the ML Engineer II will collaborate with a diverse group of data scientists, analysts, engineers, and product managers to work on exciting projects and contribute to the growth of Equip.
Responsibilities
- Design and build end-to-end ML and AI pipelines, including training, fine-tuning, experimentation, and deployment, for a variety of use cases.
- Develop tools and processes that leverage ML/AI to enhance the user experience, glean insights from large datasets, and increase operational efficiency.
- Monitor, evaluate, and optimize models for better performance and outcomes.
- Collaborate with cross-functional team members to scope and define project requirements, develop solutions, and deliver scalable and effective ML/AI models.
- Research state-of-the-art advancements in ML/AI to guide our continuous improvement in the data space.
- Perform other duties as assigned.
Qualifications
- A bachelor’s or master’s degree in Computer Science, Statistics, Mathematics, Operations Research, Engineering, or other quantitative field.
- 2+ years of demonstrated experience developing, training, evaluating, testing, deploying, monitoring, and iterating on production-level models and ML/AI pipelines at scale.
- Solid understanding of software engineering principles and best practices.
- Solid knowledge of mathematics and statistics.
- Experience with large language models applied to unstructured text-based.
- Strong programming skills in Python, Python-based ML frameworks, and SQL.
- Ability to write clear, maintainable, extensible, and testable code.
- Experience with Git / GitHub.
- Demonstrated ability to communicate and collaborate with diverse, cross-functional teams.
- Organized and results-driven.
- Comfortable in a fast-paced environment that is subject to rapid change and innovation.
Physical Demands
- Work is performed 100% from home with no requirement to travel. 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 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.
- As an equal opportunity employer, we provide equal opportunity in all aspects of employment, including recruiting, hiring, compensation, training and promotion, termination, and any other terms and conditions of employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, familial status, age, disability, weight, and/or any other legally protected classification protected by federal, state, or local law.