Interested in this AI/ML Engineer role at hims & hers?
Apply Now →About This Role
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:
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Hims \& Hers is seeking a highly motivated and experienced Privacy \& AI Counsel to join our dynamic and collaborative Legal team. In this pivotal role, you will provide practical and strategic legal guidance across the company on matters related to privacy, AI, and data protection. You will be instrumental in developing and scaling our privacy and AI programs as we continue to innovate at the intersection of healthcare, technology, and consumer products.
You’ll work cross\-functionally with teams in product, marketing, engineering, security, and compliance to ensure our data practices and digital health offerings align with evolving international legal frameworks and privacy expectations. This is a fantastic opportunity for an attorney who thrives in a mission\-driven, fast\-paced environment and is excited to help shape the future of consumer healthcare.
You Will:
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- Serve as a subject matter expert on privacy laws and apply your expertise across all business functions within our global organization.
- Lead AI and privacy\-related legal reviews of products and features, ensuring privacy\-by\-design principles are integrated early in the development process.
- Provide actionable business guidance on complex data use cases, including AI initiatives
- Work closely with the Product, AI, Marketing, and Engineering teams to align legal requirements with operational controls and business processes.
- Develop and maintain internal policies and playbooks to provide teams clear legal frameworks, risk considerations, and best practices for responsible AI use.
- Collaborate with the Legislative and Public Policy teams to evaluate proposed AI and privacy laws and support the company’s advocacy efforts.
- Support and scale our privacy and AI programs by leading impact assessments (e.g., DPIAs, AI risk assessments) and documenting data processing activities.
- Monitor legal and regulatory developments in privacy and AI matters and translate them into clear, business\-friendly guidance.
- Support incident response for privacy and AI\-related matters, collaborating with cross\-functional partners from the detection stage to mitigation.
You Have:
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- J.D. from an ABA\-accredited law school; active license to practice law in at least one U.S. jurisdiction.
- 5\+ years of experience advising on privacy and data handling at a top law firm or in\-house legal department.
- Expertise in consumer privacy laws, including comprehensive state and consumer health data laws, consumer protection regulations, AI laws, and healthcare privacy frameworks
- A strong track record of building cross\-functional relationships across AI, Product, Marketing, and Engineering teams to provide strategic and practical counsel.
- Experience negotiating U.S. and international privacy and AI contracts, including DPAs and BAAs.
- Sharp legal judgment and problem\-solving skills, with the ability to clearly explain complex legal concepts to cross\-functional teams.
- Comfortable working in a fast\-paced, high\-growth environment with shifting priorities.
Preferred Skills:
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- Prior experience in a healthcare, telehealth, or consumer\-facing company is highly desirable.
- Working knowledge of privacy and/or AI tools for managing data inventories, risk assessments, consumer consent, and data subject requests.
- CIPP/US, CIPP/C or CIPP/E certification is a plus.
- Experience in health tech, digital health, or telehealth environments.
Our Benefits (there are more but here are some highlights):
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- 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.
Compensation Range: $170K \- $205K
Salary Context
This $170K-$205K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At hims & hers, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. Disclosed range: $170K to $205K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
hims & hers AI Hiring
hims & hers has 2 open AI roles right now. They're hiring across MLOps Engineer, AI/ML Engineer. Based in US. Compensation range: $205K - $250K.
Location Context
AI roles in Austin pay a median of $215,300 across 523 tracked positions. That's 8% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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