Full-Time Lead Machine Learning Engineer

Hims & Hers Health, Inc. (better known as 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 revolutionizing telehealth for providers and their patients alike.

Making personalized solutions accessible is of paramount importance to Hims & Hers and we are focused on continued innovation in this space.

Hims & Hers offers nonprescription products and access to highly personalized prescription solutions for a variety of conditions related to mental health, sexual health, hair care, skincare, heart health, and more.

About the Role: How can we use data to build systems that enable easier and more affordable access to health care? In this role as Lead Machine Learning Engineer you will work with engineers, data scientists, product managers, and others to implement and productionize data-driven products that help advance our mission to eliminate stigmas and break down barriers to access.

1. Collaborate with ML engineers, data scientists, product managers and other engineering teams to build, deploy, and scale machine learning-based systems, ensuring their reliability and performance in production
2. Help guide and make technical decisions based on your knowledge of productionizing data science and ML models, balancing innovation and operational efficiency
3. Evaluate and implement state-of-the-art tools and frameworks, bringing a broad awareness of the machine learning and LLM production landscape into the company
4. Mentor and be mentored by other engineers
5. Actively participate in retrospectives and help drive continuous improvement in our process and culture

You Have:

• 10+ years working in Engineering and/or Machine Learning Engineer with a proven record of developing and maintaining machine learning production systems
• Expertise with the modern machine learning orchestration and deployment tool stack (such as Databricks MLFlow, AWS SageMaker, Metaflow)
• Proficiency in Python and machine learning libraries and frameworks (e.g., PyTorch, Scikit-learn, Tensorflow)
• Strong understanding of MLOps principles and experience automating workflows for model training, deployment, and monitoring
• Familiarity with machine learning fundamentals, statistical modeling techniques, and data preprocessing pipelines
• Experience with LLM deployment tooling is a plus
• Masters in Computer Science or related fields
• A collaborative mindset and excellent communication skills

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