hims & hers

Staff Machine Learning Engineer

hims & hers

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $210,000 - $230,000 per year

Job Level

Lead

Tech Stack

AWSPythonPyTorch

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.
  • 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

Requirements

  • 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