Staff Software Engineer, AI & Recommendations Platform

hims-and-hers; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary

Equity compensation

Unlimited PTO

Health benefits

ESPP

401k

Job summary

Hims & Hers is seeking a Staff Software Engineer on the AI team to lead the design and development of scalable backend systems and platform services that power treatment recommendations and personalization. You will partner with ML engineers to productionize models and embed intelligent decisioning into clinician and patient workflows.

This role focuses on building robust, cloud-native architectures and data pipelines, with opportunities to influence long-term AI strategy across healthcare

Qualifications

• 8+ years of professional software engineering experience.
• Backend, distributed systems, APIs, and cloud-native architectures.
• Experience leading large technical initiatives and influencing architecture across teams.
• Experience building data-intensive applications with ML or recommendation systems.
• Strong proficiency in Python and modern software practices.
• Experience integrating ML models and recommendation engines into production systems.
• Familiarity with ML lifecycle concepts: training, evaluation, deployment, monitoring and experimentation.

Responsibilities

• Lead the design and development of scalable backend systems and APIs for treatment recommendations and personalization.
• Architect infrastructure to support experimentation, recommendation engines, and AI-powered experiences.
• Collaborate with ML engineers to productionize models and integrate decisioning into workflows.
• Design and implement highly reliable, observable distributed systems.
• Drive platform investments in tooling, testing infrastructure, and data pipelines.
• Partner with cross-functional teams to establish reusable patterns and best practices.

Skills

Python

Backend engineering

Distributed systems

APIs

Cloud-native architectures

Machine learning / recommender systems

Education

Advanced degree in Computer Science or ML

Tools

AWS

Kubernetes

Databricks

MLflow

Airflow

Job description

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:

• 8+ 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

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 [e-mail] 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.