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 use vast amounts of proprietary and internet-scale healthcare data to build systems that enable access to significantly better healthcare?
As a Staff Software Engineer on the AI team, you will play a key technical leadership role in evolving AI & Recommendations platform. You will help build the systems, infrastructure, and services that power treatment recommendations, provider decision support and experimentation across multiple healthcare verticals.
This role is ideal for an engineer who is passionate about building scalable platforms and production systems while leveraging machine learning and AI technologies to solve complex healthcare problems. You will work across the stack—from APIs and platform infrastructure to recommendation systems and LLM-powered applications—to enable intelligent, personalized care at scale.
You Will:
Lead the design and development of scalable backend systems, APIs, and platform services that power treatment recommendations and personalization.
Architect and build the infrastructure that enables experimentation, recommendation engines, and AI-powered healthcare experiences
Partner with Machine Learning engineers to productionize models and integrate intelligent decisioning into customer and provider workflows
Design and implement highly reliable, observable, and maintainable distributed systems
Drive platform investments including self-service tooling, testing infrastructure, unified decisioning frameworks, and data pipelines
Collaborate with vertical engineering teams to establish reusable patterns, frameworks, and best practices that enable independent innovation
Evaluate and integrate emerging AI and LLM technologies where they can improve provider efficiency, patient outcomes, or operational scale
Lead complex technical initiatives that span multiple teams and systems
Mentor engineers and provide technical leadership through design reviews, architecture discussions, and hands-on implementation
Influence the long-term technical direction of the MedMatch platform and broader AI ecosystem
You Have:
5+ years of professional software engineering experience building and operating production systems at scale
Strong expertise in backend engineering, distributed systems, APIs, and cloud-native architectures
Demonstrated success leading large technical initiatives and influencing architecture across teams
Experience building data-intensive applications and services that leverage machine learning or recommendation systems
Strong proficiency in Python and modern software development practices
Experience integrating ML models, recommendation engines, or LLM-powered applications into production systems
Familiarity with ML lifecycle concepts including training, evaluation, deployment, monitoring, and experimentation
Experience with cloud platforms and modern infrastructure tooling (AWS, Kubernetes, Databricks, MLflow, Airflow, etc.) is a plus
Ability to balance short-term product delivery with long-term platform scalability and maintainability
Excellent collaboration and communication skills, with the ability to work effectively across engineering, product, data science, and clinical stakeholders
Nice to Have:
Experience building recommendation systems, ranking systems, personalization platforms, or decision-support systems
Experience in healthcare, health tech, or other regulated environments
Advanced degree in Computer Science, Machine Learning, or a related field
Our Benefits (there are more but here are some highlights):
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 accommodations@forhims.com 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.
Compensation Range: $195K - $240K