Senior Machine Learning Engineer

2 Months ago • 4 Years + • Research Development • $160,000 PA - $180,000 PA

Job Summary

Job Description

As a Senior Machine Learning Engineer, you will be crucial in driving better health outcomes by engaging members through the Health Engine. You will be involved in the entire ML lifecycle, from framing business questions and data analysis to model building and deployment. Key responsibilities include implementing and optimizing information retrieval models, staying updated on the latest advancements, and collaborating within a team. You will work with diverse data sources, contribute to internal ML libraries, and provide ML expertise within the team and the organization. The role requires experience in a production environment, with a strong command of Python and SQL. You will be expected to ensure the security of Well systems and data, including sensitive member data, following Well data and security policies and HIPAA guidelines.
Must have:
  • Implement and optimize information retrieval models for search/recommendation.
  • Experience using Python for machine learning (pytorch, huggingface, scikit-learn).
  • Proficient with SQL and databases.
  • Experience executing analyses in the cloud (GCP, AWS).
  • Advanced degree (MS or PhD) in a quantitative field.

Job Details

Company: The mission of Well (https://www.well.co/) is to transform healthcare through our unique impact to our members' health and happiness. We do this through our differentiated consumer experience and world-class data and analytics engine that drive engagement and behavior change. Our product -- a consumer health engagement platform -- integrates concierge services, behavioral health, telemedicine, care management and wellness services to drive sustained engagement, lower costs and improve the health of members. In addition to our product, we know our team makes us unique. We’re a highly diverse and engaged organization whose employees are passionate about the mission of the company and whose management is passionate about the employees.

Position Title: Senior Machine Learning Engineer

Reporting To: Senior Manager, Data Science

Location: Chapel Hill, NC; New York, NY: Boston, MA

Compensation Information: Senior Machine Learning Engineer $160,000-$180,000, based on qualifications, plus bonus potential 

Position Summary:

The overall goal is to engage our members to drive better health outcomes. Our modeling and optimization platform (the Health Engine) contributes directly to our product through machine learning, statistics, analysis, and computation. The next member of our team will drive ML projects from beginning to end: frame business questions, collect and analyze data, research, prototype models, build/deploy pipelines, and share insights. They will work collaboratively within a team aiming to make a positive impact on the organization and on our members’ overall health.

Our primary ML task is retrieving information, either information relevant to what was searched for, or retrieving information to recommend to the user. We’re looking for someone who is experienced in implementing information retrieval models.  This candidate is excited about the field and stays current on the latest development. The ideal candidate will be able to work off of and contribute to our libraries. The ideal candidate can work on any part of the ML lifecycle – data gathering and processing, model development, performance evaluation, model deployment, performance monitoring. This candidate needs to be experienced working in a production environment in a team setting. We also expect this candidate to pitch in on tasks outside of the focus area. The ideal candidate has strong command of Python and SQL.

Key Responsibilities:

  • Implement and optimize information retrieval models for search and recommendation tasks.
  • Stay current with the latest developments and advancements in the field of machine learning and information retrieval.
  • Leverage and utilize a wide range of disparate data sources across our ecosystem and within healthcare (app, claims, EHR, wearables).
  • Engage in all stages of the ML lifecycle: Data gathering and preprocessing, model development and performance evaluation, model deployment and performance monitoring.
  • Contribute to and build upon existing internal ML libraries. 
  • Take on additional tasks and contribute to areas outside of the primary focus when needed.
  • Provide ML expertise within the team and across the organization.
  • Take personal responsibility for keeping all Well systems and data, including sensitive member data, secure and safe, according to Well data and security policies and HIPAA guidelines

Preferred Qualifications:

  • 4+ years of work/industry experience in data science or machine learning roles
  • Advanced degree (MS or PhD) in a quantitative field. Strong grasp and theoretical understanding of machine learning
  • Demonstrated experience using Python for machine learning (pytorch, huggingface, scikit-learn, sentence-transformers, xgboost, polars/duckdb, lancedb, langchain)
  • Proficient with SQL and databases
  • Expertise using Unix/OSX from the command line, version control (Git), and general software development best practices for contributing to a collaborative code base
  • Experience executing analyses in the cloud (GCP, AWS)
  • Collaborate effectively within a production team environment.

Additional Job Information

Well is on a mission to redefine the healthcare experience. This is an opportunity to re-shape healthcare for America. We are developing solutions to improve the quality and affordability of healthcare.  We welcome team members who are passionate about that mission. We embrace diversity and are committed to building an inclusive team.

Well is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.  We seek diversity and encourage individuals from underrepresented groups to apply.

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Chapel Hill, North Carolina, United States (On-Site)

Boston, Massachusetts, United States (On-Site)

United States (Remote)

Chapel Hill, North Carolina, United States (Remote)

Chapel Hill, North Carolina, United States (Remote)

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