Website Lyra Health

About Lyra Health
Lyra 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 elite provider network, 2.5 million people can receive best care and feel better, faster. Founded by David Ebersman, former CFO of Facebook and Genentech, Lyra has raised more than $680 million.

At 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 Software Engineering Manager 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 physicians, therapists, data scientists, and product managers

Be a hands-on technical leader for an machine learning engineering team responsible for designing, developing, reviewing, and deploying core ML products and services
Be the engineering owner for core pieces of our ML models, data APIs, and ML infrastructure
Manage, scale, and mentor the ML engineering team
Work with stakeholders on priorities and roadmap for ML models and data API’s
Plan and manage bi-weekly sprint boards

4+ years working as an engineering manager focused on machine learning and large scale production applications
A track record of scaling and building ML engineering teams
Experience delivering production-level machine learning models and data APIs for production use
Expertise with hands-on experience in Python, Java (Kotlin a plus)
Expertise in algorithms, optimization techniques, and machine learning
Strong communication skills and ability to generate consensus and buy-in within the team and stakeholders
Organizational skills and the ability to simplify complex problems and prioritize what matters most for the sake of the team and the business

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