Machine Learning Infrastructure Engineer
What you will be doing
About this Opportunity:
The ML Platform team's mission is to build top-notch systems for deploying and serving machine learning models in a production environment. As a team member, you’ll contribute toward a set of APIs, systems, and platforms to help unlock critical algorithmic capabilities and self-service platforms and tools to facilitate scalable research & development for our data scientists. We are driven by the elegance of beautiful abstractions that scale and age well, and by helping our colleagues run production algorithms with less friction, ultimately increasing the velocity at which the business can progress.
What you will do:
- Build critical infrastructure that powers ML.
- Help us to design, build, and maintain services and frameworks for ML model training and serving that are scalable and resilient.
- Be involved in the day-to-day operations of the team, including maintaining and improving our current platform, consulting, and supporting full-stack data scientists.
- Have autonomy to help shape the future of the ML platform at our company by bringing your ideas on improving and codifying what we do and how we do it.
- Collaborate with different teams of data scientists, engineers, and business partners to solve distributed systems and business problems in a scalable way.
- Join a team that has high visibility across the organization.
- Share ideas and direct the team’s investment in impactful directions.
- Contribute to a culture of technical collaboration and scalable resilient systems.
The ML Platform team's mission is to build top-notch systems for deploying and serving machine learning models in a production environment. As a team member, you’ll contribute toward a set of APIs, systems, and platforms to help unlock critical algorithmic capabilities and self-service platforms and tools to facilitate scalable research & development for our data scientists. We are driven by the elegance of beautiful abstractions that scale and age well, and by helping our colleagues run production algorithms with less friction, ultimately increasing the velocity at which the business can progress.
What you will do:
- Build critical infrastructure that powers ML.
- Help us to design, build, and maintain services and frameworks for ML model training and serving that are scalable and resilient.
- Be involved in the day-to-day operations of the team, including maintaining and improving our current platform, consulting, and supporting full-stack data scientists.
- Have autonomy to help shape the future of the ML platform at our company by bringing your ideas on improving and codifying what we do and how we do it.
- Collaborate with different teams of data scientists, engineers, and business partners to solve distributed systems and business problems in a scalable way.
- Join a team that has high visibility across the organization.
- Share ideas and direct the team’s investment in impactful directions.
- Contribute to a culture of technical collaboration and scalable resilient systems.