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Staff Machine Learning Engineer

Hims & Hers

Hims & Hers

Software Engineering
United States · Remote
USD 210k-230k / year + Equity
Posted on Aug 19, 2025

Location

US Remote

Employment Type

Full time

Location Type

Remote

Department

ENGINEERING

Compensation

  • An estimate of the current salary range is for US-based candidates is: $210K – $230K • Offers Equity

Outlined above is a reasonable estimate of H&H’s compensation range for this role for US-based candidates. If you're based outside of the US, your recruiter will be able to provide you with an estimated salary range for your location.

The actual amount will take into account a range of factors that are considered in making compensation decisions, including but not limited to skill sets, experience and training, licensure and certifications, and location. H&H also offers a comprehensive Total Rewards package that may include an equity grant.

Consult with your Recruiter during any potential screening to determine a more targeted range based on location and job-related factors.

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 data to build systems that enable access to significantly better health care? In this role as Staff Machine Learning Engineer, you will play a technical leadership role in leading the development and deployment of machine learning models that drive care personalization, treatment recommendations, and automation across our platform. Your work will directly impact strategic components of MedMatch, our AI-powered system that enhances provider-patient interactions, optimizes treatment recommendations, and expands into new verticals.

You Will:

  • Lead and contribute to the design and deployment of ML and LLM models for recommendation systems and personalized treatment strategies

  • Work extensively with Python and ML libraries like PyTorch to scale and refine complex models

  • Write high-quality, scalable, and production-ready code to support advanced ML applications

  • Collaborate with engineers and product managers to deliver ML models integrated into real-world systems

  • Design, scale, and improve ML infrastructure components to accelerate model training, evaluation, and deployment

  • Research and integrate cutting-edge ML tools and frameworks, keeping the company at the forefront of ML and LLM advancements

  • Mentor engineers within and across squads, sharing expertise in ML modeling, deployment, and best practices

  • Drive improvements in team process and foster cross-team collaboration

You Have:

  • 5+ years of experience in Machine Learning and/or Engineering, with a deep focus on hands-on model development and deployment

  • Expert-level proficiency in Python and deep experience in ML frameworks like PyTorch

  • Proven success leading ML model development and deployment efforts across multiple projects

  • Strong background in LLMs and NLP applications, including applications like summarization and chatbots

  • Proficiency in ML deployment best practices, with the ability to bring models from research to production

  • Experience with ML infrastructure tools (e.g., Databricks, MLFlow, AWS SageMaker) is a plus

  • A Master’s degree in Computer Science, Machine Learning, or a related field (not strictly required)

  • A collaborative mindset, strong problem-solving skills, and the ability to influence direction across teams and technical areas

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: $210K - $230K