Machine Learning Infrastructure Engineer

About Lyra HealthLyra is transforming mental health care through technology with a human touch to help people feel emotionally healthy at work and at home. We work with industry leaders, such as Morgan Stanley, Uber, Amgen, and other Fortune 500 companies, to improve access to effective, high-quality mental health care for their employees and their families. With our innovative digital care platform and global provider network, 10 million people can receive the best care and feel better, faster. Founded by David Ebersman, former CFO of Facebook and Genentech, Lyra has raised more than $900 million.
About the RoleAt Lyra we believe that data-driven technology and decision making is a critical part of solving the thorny, complex challenges of provider quality and accessibility in a broken system. We are looking for an experienced Machine Learning Infrastructure Engineer who cares about impact, ownership, cross-functional projects, and mentorship.  Lyra is for you if you: Want to work with brilliant people solving hard problems; Have a passion for social impact and helping people when they are most vulnerable; Like to collaborate across teams with engineers, data scientists, and product managers.
This role can be full-time in our Burlingame, CA headquarters or virtual based in the United States.

Responsibilities

• Be part of a team working on building out scalable infrastructure to train, evaluate, deploy, perform inference and monitor our ML models
• Create data systems to collect, clean, label and store data used for model features
• Deploy and manage various applications in our Kubernetes clusters
• Work with stakeholders on requirements and solutions for ML infrastructure
• And of course, you will be coding every day!

Qualifications

• 2+ years of industry experience building production level ML infrastructure and data pipelines
• Ability to write high-quality code in Python, Java or Scala
• Experience building RESTful APIs
• Experience working with Docker and deploying applications to Kubernetes
• Experience with CI/CD pipelines, ideally in Jenkins
• Experience with relational and low-latency databases
• Experience with transforming data in both batch and streaming contexts
• A desire to learn new technologies quickly
• A love of building systems from scratch
• Experience working with highly sensitive data in a healthcare environment
• A track record of making quality vs. deadline tradeoffs in fast-paced environments
• Strong communication skills and ability to generate consensus and buy-in within the team
• Organizational skills and the ability to simplify complex problems and prioritize what matters most for the sake of the team and the business

Preferred Qualifications

• Experience working with ML frameworks such as Pytorch, SciKit-learn, XGboost
• Experience working with ML Ops tools such as MLFlow, Kubeflow, AWS Sagemaker
• Experience building solutions on cloud infrastructure, particularly AWS

We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age (40 or older), disability,  genetic information or any other category protected by law.