Senior Machine Learning Engineer, Well
$160-180k
All-in-one health guidance platform
Open for applications
All-in-one health guidance platform
201-500 employees
Open for applications
$160-180k
201-500 employees
Company mission
To be the world's most effective partner in the advancement of individualized health.
Role
Who you are
- 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
- 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
What the job involves
- Reporting To: Senior Manager, Data Science
- 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
- 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
Our take
Mobile health-tracking apps have become popular over the last decade, but existing platforms often provide uniform services as opposed to personalizing each user's experience. In addition to this, incentives to regularly use an app are generally focused on mobile notifications and manual tracking systems, features that require manual data entry and are easy to ignore.
Well provides a digital health platform that leverages member health data to provide users with a personalized and all-in-one platform for improving their health. Instead of relying on notifications and uniform systems, member data is used to deliver daily health recommendations from AI clinicians, loyalty rewards, and direct support tools.
With many apps on the market for different health points, the digital health tracking landscape is very saturated, yet Well is taking a unified approach to providing personalized and authentic experiences for users. The platform aims to provide guidance that is actionable and engaging, as opposed to just another mobile app that is used on an occasional health kick.
Freddie
Company Specialist at Welcome to the Jungle
Insights
40% employee growth in 12 months
Glassdoor (3.3)
Company
Funding (last 2 of 5 rounds)
Apr 2025
$30m
LATE VC
Apr 2022
$71.9m
GROWTH EQUITY VC
Total funding: $236.9m
Company benefits
- A hybrid work policy that allows for both in-person and remote work for most roles
- 18 days of paid time off and 9 paid holidays
- Volunteer Time Off program to support individual values and volunteer activities that enhance and serve the communities in which we live and work
- Free coffee and snacks in the office as well as fun social events
- Parental leave for new parents, regardless of gender, whether through birth or adoption of a child, as a benefit of employment in order to support the health and wellbeing of the whole family and equitable opportunity for career advancement
- Health, dental, and vision insurance
- Tax-advantaged HSA or FSA for healthcare, dependent care, and commuter benefits
- 401(k) and short- and long-term disability and life insurance coverage at no cost to the employee
- Learning Time Off each quarter to support learning and career development
Company HQ
Chapel Hill, NC
Leadership
Gary Loveman
(Co-Founder, Chairman & CEO)They started their career as an HBS professor following an Economics Ph.D. at MIT. They worked as EVP of Aetna in Consumer Health Services and as CEO of Caesar's Entertainment Company, before co-founding Well with David.
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