Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve.
Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about and hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals.
About the Role:How can we design and scale the systems that make advanced AI/ML possible in healthcare? In this role as Sr. Staff Machine Learning Systems Engineer, you will lead the development of foundational ML ecosystem components that power our various AI models’ training, evaluation, deployment, and monitoring.
We are seeking deep specialists who bring world-class expertise in one of three critical domains:
ML data pipelines: building reproducible, high-quality data ingestion, transformation, and feature engineering pipelines at scale.
ML evaluation algorithms and infrastructure: designing and scaling evaluation frameworks, algorithms, and infrastructure for model quality, performance monitoring, and drift detection.
ML systems debug and visualization tooling: creating tools and platforms to debug, visualize, and interpret ML models and pipelines, accelerating productivity and system reliability.
Your work will directly shape how we operationalize ML by ensuring the systems behind model development and deployment are robust, transparent, and future-proof.
You Will:Own and drive architectural decisions within your area of ML systems expertise (data pipelines, evaluation infra, or debug/visualization tooling).
Build, optimize, and scale infrastructure that enables reproducible, efficient, and trustworthy ML workflows.
Write and review high-quality, production-ready code supporting foundational ML platforms and services.
Partner with ML engineers, data scientists, and platform engineers to ensure infrastructure meets research and production needs.
Drive adoption of modern ML systems and platform practices, contributing to long-term organizational technical maturity.
Mentor senior and staff-level engineers, guiding best practices within your specialization.
Champion a culture of reliability, scalability, and engineering rigor across ML systems initiatives.
8+ years of experience in distributed systems, data engineering, or ML infrastructure, with a track record of technical leadership at scale.
Expert-level proficiency in one of the following areas:
ML data pipelines: designing and maintaining feature stores, dataset versioning systems, and high-throughput ML pipelines.
ML evaluation algorithms and infrastructure: building large-scale evaluation algorithms, frameworks, benchmarking systems, and continuous monitoring.
ML systems debug and visualization tooling: developing debugging frameworks, visualization tools, and interpretability systems to enhance developer productivity and model reliability.
Strong programming skills in Python, with experience in systems languages such as Go, Java, or C++ as a plus.
Solid understanding of end-to-end ML workflows, with the ability to collaborate effectively across infrastructure and modeling teams.
A Master’s degree or PhD in Computer Science, ML Systems, or a related field (not strictly required).
Exceptional communication and cross-org leadership skills, with the ability to align diverse stakeholders around ML systems strategy.
Competitive salary & equity compensation for full-time roles
Unlimited PTO, company holidays, and quarterly mental health days
Comprehensive health benefits including medical, dental & vision, and parental leave
Employee Stock Purchase Program (ESPP)
401k benefits with employer matching contribution
Offsite team retreats
We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you're excited about this role, we encourage you to apply—even if you're not sure if your background or experience is a perfect match.
Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at [email protected] and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address.
To learn more about how we collect, use, retain, and disclose Personal Information, please visit our Global Candidate Privacy Statement.
Top Skills
Similar Jobs
What you need to know about the Charlotte Tech Scene
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus