Sr. AI/ML Infrastructure Engineer

United States

Lyra Health

Lyra is your partner in building a culture that celebrates mental well-being. Learn more about how to partner with Lyra and transform workforce mental health.

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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 complex challenges of provider quality and accessibility that are critical to providing high quality care to users. We are looking for an experienced AI/ML Infrastructure Engineer who cares about impact, ownership, cross-functional projects, and mentorship.
This role can be carried out from our Burlingame, CA headquarters, hybrid, or fully remote/virtually. Remote candidates must be physically located within the United States.

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

Responsibilities

  • Be part of a team working on building out scalable infrastructure to train, evaluate, deploy, perform inference and monitor our ML models
  • Build, deploy and maintain generative AI services & applications 
  • Create data systems to collect, clean, label and store data used for model features
  • Deploy and manage various applications in our Kubernetes clusters
  • Collaborate with Machine Learning engineers to build & support state of the art experimentation platforms, training frameworks and associated tools
  • Work with stakeholders on requirements and solutions for ML infrastructure
  • And of course, you will be coding every day!

Qualifications

  • 5+ years of industry experience building production level ML platforms and infrastructure, including experience building ML systems/pipelines from the ground-up.
  • Ability to write high-quality code in Python, Java or Scala
  • Experience building production ready RESTful APIs, as well as having scaled platforms in production to a large number of users.
  • A desire to own large parts of an ML Platform, with a strong understanding of ML models & principles.
  • Experience working with containers and deploying applications to Kubernetes
  • Experience with LLMs and building infrastructure to support LLM applications
  • Experience with relational and low-latency databases
  • Experience with transforming data in both batch and streaming contexts
  • A desire to learn new technologies quickly, and a proven track record of making quality vs. deadline tradeoffs in fast-paced environments.
  • Ability to scope out a large project and manage it through project delivery 
  • 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 highly sensitive data in a healthcare environment
  • 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, disability, genetic information or any other category protected by law.
By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra.  We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR.  Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives.  If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form.  This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice."
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: APIs AWS Generative AI Java Kubeflow Kubernetes LLMs Machine Learning MLFlow ML infrastructure ML models Pipelines Privacy Python PyTorch SageMaker Scala Scikit-learn Streaming XGBoost

Regions: Remote/Anywhere North America
Country: United States

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