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We are seeking an innovativeto join the Operations Engineering and Architecture group. This dedicated team is focused on driving Operations technology target state and delivering tangible reductions in process friction, errors, and manual effort. In this role you will be responsible for driving and contributing to the technical direction of our products and services, instilling engineering best practices into the team, and promoting cultural change across the organization. You will also work with Generative AI technologies, such as GPT-4, embedding their capabilities through prompt engineering in our systems.
What you’ll do:
Contribute to both, engineering and research
Take a product-focused approach and build solutions that are robust, scalable, and easy to use
Work in a fast-paced environment tackling cutting-edge problems by constantly testing and learning
Pair programming for our products, be lean in your approach and remove bureaucracy where you see it
Deliver fast, iterating and pivot as you go, rather than defining the perfect solution upfront
Develop foundational components and mature technology capabilities in AI and LLMs
Drive adoption across the enterprise
What we’ll need from you:
Deep hands on knowledge of Kubernetes, developing backend platforms and engineering solutions that scale
Fluency in at least two programming language, with preference for Python, Javascript/Typescript, Golang
Experience designing control and sandboxing systems for AI research
Pytorch, TensorFlow experience
Experience maintaining and/or contributing to bug bounty and responsible disclosure programs
Understanding of language models and transformers
Rich understanding of vector stores and search algorithms
Large-scale ETL development
Direct engineering experience of high performance, large-scale AI/ML systems
Have experience supporting fast-paced startup engineering teams
Have used LangChain and even contributed to the project.
As Generative AI is a relatively new and growing space, as a result, we ask that you share with us a specific AI engineering projects on LLMs that you’re proud of in your application. Ideally these projects should show off complex and clever architectures or a systematic evaluation of an LLM’s behavior.
Time Type:
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