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
In this role, you will:
- 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!
We are looking for someone with:
- 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
Nice to haves:
- 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
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