Senior/ Staff ML Engineer, Recommendations Systems

Senior/ Staff ML Engineer, Recommendations Systems

About us: 

Grow Therapy is on a mission to serve as the trusted partner for therapists growing their practice, and patients accessing high-quality care. Powered by technology, we are a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Following the mass increase in depression and anxiety, the need for accessibility is more important than ever. To make our vision for mental healthcare a reality, we’re building a team of entrepreneurs and mission-driven go-getters. Since launching in February 2021, we’ve empowered more than ten thousand therapists and hundreds of thousands of clients across the country and insurance landscape. We’ve raised more than $178mm of funding from Sequoia Capital, Transformation Capital, TCV, SignalFire, and others.

What You’ll Be Doing: 

We are looking for a machine learning engineer who has worked in search and personalization and is scrappy and pragmatic, using data and deductive reasoning to apply practical approaches into their algorithms. They’ll work directly with our Director of Data to create a search algorithm that improves the matching experience between clients and providers. Your responsibilities will include:

  • Design, develop, and deploy a scalable search ranking algorithm to enhance user experience on the Grow Therapy platform.
  • Collaborate with data scientists to define and extract relevant features from large datasets.
  • Implement machine learning models for search ranking, including training, evaluation, and optimization.
  • Develop and maintain data pipelines and infrastructure to support the continuous improvement of the search algorithm.
  • Comfortable with A/B testing design and analysis of performance differences between existing and new model variations to ensure confidence in positive business outcome improvements.

You’ll Be a Good Fit If: 

  • Proven experience in building and deploying machine learning models in the context of search ranking or recommendation systems.
  • 5+ years of experience as a ML engineer or Data Scientist- ideally at an early stage or high growth startup - specializing in machine learning algorithms
  • Past experience building algorithms from 0->1 and an entrepreneurial mindset
  • Strong programming skills in Python and SQL. 
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Proficiency in working with large datasets, data preprocessing, and feature engineering.
  • Knowledge of information retrieval, natural language processing, and ranking algorithms.
  • Ability to work cross functionally with growth, engineering, product, and an executive team 
  • Knowledge and experience in best practices in applying MLOps in an organization with an emphasis on continuous development and deployment.

Salary Range: $170,000 - $245,000

Benefits

  • The chance to drive impact within the mental healthcare landscape from day one
  • Comprehensive health insurance plans, including dental and vision
  • Our dedication to mental health guides our culture. Wellness benefits include (but are not limited to):
    • Flexible working hours and location (remote OR in-office, your choice!)
    • Flexible Time Off 
    • Company-wide winter break 
    • Mental health mornings (2 hours each week)
    • Team meditation
    • Wellness Stipend
    • In-office lunch and biweekly remote lunch on us! 
  • Continuous learning opportunities 
  • Competitive salary 
  • The opportunity to help build a rapidly scaling start-up organization by taking strong ownership of your work, mentorship, and our unbounded leadership opportunities 

#LI-REMOTE

Grow Therapy is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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