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As a Machine Learning Systems Engineer on the AI & ML Platform team, you will build and scale the core infrastructure to allow software engineers, ML engineers & data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines. Along with that, you will build systems for product teams like Jira & Confluence to provide access to curated LLMs. You will use your software development expertise to solve difficult problems, tackling infrastructure and architecture challenges. You will have the opportunity to lead engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results.
Job Responsibility:
Build and scale the core infrastructure to allow software engineers, ML engineers & data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines
Build systems for product teams like Jira & Confluence to provide access to curated LLMs
Use software development expertise to solve difficult problems, tackling infrastructure and architecture challenges
Lead engineers to drive involved projects from technical design to launch
Collaborate with other teams and internal customers to set expectations, gather input and communicate results
Regularly tackle complex problems in the team, from technical design to launch
Routinely tackle complex architecture challenges and defines coding standards & patterns for the team
Lead the team through times of ambiguity, help them adapt and deliver positive impact
Mentor junior members on the team
Requirements:
Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin)
Understanding and experience with Machine Learning project lifecycle and tools
Understanding of LLMs, best deployment practices and inference optimisation
Experience in building and implementing high-performance RESTful micro-services
Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking)
Experience with Continuous Delivery and Continuous Integration
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