Scale Engineer

Staff Software Engineer, AI & Recommendations Platform

Staff Engineer · Staff · Full Time · Remote

US Remote · RemoteUSD 195k – 240k2mo ago
Apply for this role

Opens Hims & Hers's application page

Role

What you'll do.

Staff Software Engineer on Hims & Hers' AI & Recommendations Platform team, responsible for designing and leading scalable backend systems, ML integration infrastructure, and experimentation platforms that power personalized treatment recommendations and provider decision support across multiple healthcare verticals. This role requires 5+ years of production systems experience with deep expertise in distributed systems, Python, and ML productionization, combining technical leadership with hands-on architecture and implementation across the full stack.

Responsibilities

  • Backend Systems Architecture & Leadership: Lead the design, development, and maintenance of scalable backend systems, APIs, and platform services that power personalized treatment recommendations and patient/provider personalization engines. Architect highly reliable, observable, and maintainable distributed systems capable of handling healthcare-scale data volumes while ensuring HIPAA compliance and operational excellence.
  • ML Productionization & AI Integration: Partner with Machine Learning engineers to operationalize predictive models and integrate intelligent decisioning into customer-facing and provider workflows. Design and implement production pipelines that enable real-time model serving, continuous evaluation, and safe model deployment across multiple healthcare verticals with rigorous monitoring and rollback capabilities.
  • Experimentation Platform Infrastructure: Architect and build the core infrastructure enabling experimentation, A/B testing frameworks, and ML-powered healthcare experiences. Develop unified decisioning frameworks that allow independent teams to safely experiment with treatment recommendations, personalization algorithms, and clinical decision support systems while maintaining data integrity and audit trails.
  • Platform Investment & Self-Service Tooling: Drive strategic platform investments including self-service developer tooling, comprehensive testing infrastructure, data pipeline orchestration, and reusable ML integration patterns. Build capabilities that enable vertical engineering teams to independently innovate while adhering to company-wide standards for reliability, observability, and compliance.
  • Emerging Technology Evaluation & Integration: Evaluate and strategically integrate cutting-edge AI and Large Language Model technologies where they demonstrably improve provider efficiency, enhance patient outcomes, or enable operational scale. Lead proof-of-concepts and production implementations of LLM-powered applications including clinical documentation assistance, treatment optimization, and provider decision support systems.
  • Cross-Team Technical Leadership & Mentorship: Lead complex technical initiatives spanning multiple engineering teams and systems, establishing architectural patterns and best practices across the AI & Recommendations platform ecosystem. Mentor engineers through rigorous design reviews, architecture discussions, hands-on implementation support, and knowledge transfer to develop the next generation of platform leaders.
  • Strategic Technical Direction & Influence: Influence the long-term technical vision of the MedMatch platform and broader AI infrastructure. Collaborate with engineering, product, data science, and clinical stakeholders to align technical strategy with business objectives, ensuring the platform scales efficiently, maintains clinical integrity, and adapts to evolving healthcare market demands.

Qualifications

What we look for.

Technical

  • Backend Systems & Distributed Architecture

    5+ years of professional software engineering experience designing, building, and operating production-grade backend systems at scale. Deep expertise in distributed systems design patterns, API architecture, cloud-native architectures, microservices patterns, and modern infrastructure as code approaches required.

  • Python Proficiency & Modern Development Practices

    Strong proficiency in Python with demonstrated expertise in modern software development practices including design patterns, testing strategies, CI/CD pipelines, code review culture, and collaborative engineering workflows. Experience architecting maintainable, well-documented codebases for large engineering organizations.

  • Machine Learning Integration & Productionization

    Demonstrated success integrating ML models, recommendation engines, and LLM-powered applications into production systems. Familiarity with ML lifecycle concepts including model training, evaluation metrics, deployment strategies, ongoing monitoring, retraining triggers, experimentation frameworks, and failure handling.

  • Data-Intensive Application Development

    Proven experience building data-intensive applications and services that leverage machine learning or sophisticated recommendation systems. Ability to design systems that efficiently handle feature engineering, real-time model serving, batch processing, and complex data transformations at production scale.

  • Cloud Platforms & Infrastructure Tooling

    Hands-on experience with modern cloud platforms (AWS, Google Cloud, or Azure preferred) and infrastructure tooling including Kubernetes orchestration, container technologies (Docker), data platforms (Databricks, Snowflake), ML workflow tools (MLflow, Airflow), and observability solutions for production systems.

Education

  • Bachelor's Degree in Computer Science, Software Engineering, or Related Field

    Bachelor's degree (or equivalent professional experience) in Computer Science, Software Engineering, Mathematics, Physics, or related discipline demonstrating strong foundational knowledge in algorithms, data structures, and system design principles.

  • Advanced Degree in Computer Science, Machine Learning, or Related Field (Preferred)

    Master's degree or PhD in Computer Science, Machine Learning, Data Science, or related field is a significant asset, providing deeper expertise in ML theory, statistical methods, and advanced system design concepts applicable to AI platform development.

Experience

  • Production Systems Leadership

    5+ years building, deploying, and operating production systems that serve millions of users or handle significant data volumes. Demonstrated ability to balance immediate product delivery with long-term platform scalability, maintainability, and technical debt management in complex organizations.

  • Large Technical Initiatives & Cross-Team Influence

    Proven track record leading large-scale technical initiatives that span multiple teams and systems, with demonstrated influence over architectural decisions. Experience establishing platform standards, design patterns, and best practices that enable independent team innovation while maintaining systemic integrity.

  • Recommendation & Personalization Systems

    Experience building or operating recommendation systems, ranking algorithms, personalization platforms, or decision-support systems in production environments. Understanding of collaborative filtering, content-based approaches, hybrid methodologies, or ranking optimization techniques is highly valuable.

  • Healthcare or Regulated Environment Engineering

    Experience working in healthcare, health technology, or other highly regulated environments with compliance requirements (HIPAA, GDPR, SOC 2). Understanding of audit trails, data governance, privacy-by-design principles, and clinical validation processes strengthens candidacy significantly.

Skills

Required

  • Distributed Systems Design

    Advanced ability to design, implement, and troubleshoot distributed systems handling high concurrency, fault tolerance, eventual consistency, and scalability challenges. Expertise in patterns like event sourcing, CQRS, saga patterns, and load balancing.

  • Python Backend Development

    Expert-level Python proficiency with deep understanding of async programming, web frameworks (FastAPI, Django), testing frameworks, performance optimization, and production debugging. Ability to architect Python systems for scale.

  • API Design & Platform Architecture

    Expertise designing RESTful and event-driven APIs that enable platform integration, versioning strategies, backward compatibility, rate limiting, and documentation for developer experience. Understanding of API-first architecture patterns.

  • ML Model Deployment & Serving

    Hands-on experience deploying machine learning models to production, implementing real-time serving infrastructure, batch processing pipelines, model versioning strategies, and handling model performance degradation and retraining.

  • Cloud Infrastructure & Container Orchestration

    Strong expertise with cloud platforms (AWS preferred for Hims context) and containerization technologies. Proficiency with Kubernetes, infrastructure-as-code (Terraform/CloudFormation), monitoring, logging, and cost optimization.

  • Data Pipeline & Workflow Orchestration

    Experience designing and implementing data pipelines using orchestration tools like Airflow or Dagster. Expertise in ETL design, schema management, data quality validation, and lineage tracking for complex data workflows.

  • System Design & Scalability

    Demonstrated mastery in designing systems for scale, including database selection (relational vs. NoSQL), caching strategies, asynchronous processing, data partitioning, and capacity planning for production workloads.

  • Observability & Production Debugging

    Expert-level understanding of observability principles including structured logging, distributed tracing, metrics collection, and alerting. Proven ability to diagnose and resolve production issues in complex systems.

  • Technical Leadership & Communication

    Exceptional ability to communicate complex technical concepts to diverse audiences including engineers, product managers, and non-technical stakeholders. Proven mentoring and architectural guidance capabilities.

  • Experimentation & A/B Testing Frameworks

    Understanding of statistical rigor in A/B testing, experimental design for recommendation systems, controlling for confounding variables, and interpreting results in healthcare contexts where multiple metrics may conflict.

Preferred

  • LLM Integration & Prompt Engineering

    Nice to have

    Experience integrating Large Language Models (OpenAI, Anthropic, open-source models) into production systems, including prompt engineering, RAG (Retrieval-Augmented Generation) implementations, fine-tuning strategies, and managing LLM inference costs at scale.

  • Recommendation System Implementation

    Nice to have

    Hands-on experience building collaborative filtering, content-based filtering, or hybrid recommendation systems. Knowledge of ranking algorithms, diversity/serendipity in recommendations, cold-start problems, and recommendation system evaluation metrics.

  • Healthcare Data & Clinical Concepts

    Nice to have

    Familiarity with healthcare data formats (HL7, FHIR), clinical terminology, medical ontologies (SNOMED, ICD), and understanding of healthcare workflows, provider-patient interactions, and clinical decision-support system design principles.

  • Feature Stores & ML Platforms

    Nice to have

    Experience with feature management systems, ML platform infrastructure, model registries, and ML workflow automation. Familiarity with tools like Feast, Tecton, or custom feature platforms for managing ML features at scale.

  • Real-Time Systems & Stream Processing

    Nice to have

    Experience with real-time data processing frameworks (Apache Kafka, Flink, Spark Streaming) for building low-latency personalization systems, real-time recommendations, and event-driven architectures.

  • Privacy & Compliance Engineering

    Nice to have

    Understanding of privacy engineering practices (differential privacy, federated learning), compliance requirements (HIPAA, GDPR), data governance frameworks, and secure multi-party computation for healthcare applications.

  • Graduate-Level Machine Learning Theory

    Nice to have

    Advanced understanding of machine learning theory, statistical foundations, optimization algorithms, and research papers in recommendation systems and causal inference. Experience with academic research or publishing in ML domains.

  • Cross-Functional Product Development

    Nice to have

    Demonstrated ability working effectively across engineering, data science, product management, clinical affairs, and business stakeholders to translate requirements into technical solutions with business impact.

Compensation

Pay and benefits.

Base·USD 195,000 – 240,000

Equity·Stock options

Full posting

Original listing.

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 [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.

Apply for this position

Redirects to Hims & Hers's application page.

Other roles

More at Hims & Hers.

View all 11 roles