Today’s Data Scientists are in pain - spending their time manually wrangling data, building models through slow trial and error, taking on painstaking rewrites for deployment, and dealing with countless other frustrating bottlenecks. And the tools they are using for much of this work – e.g. Jupyter notebooks and Pandas – are over a decade old.
We founded Delphina to change this: our mission is to help the world get better at using data to understand the present and predict the future. Delphina is an AI Agent for Data Science: leveraging a combination of generative AI, large scale optimization, and specialized infrastructure to automate the time-consuming but necessary tasks to build powerful ML models quickly; Delphina will identify relevant data, clean it, train models, and even productionize pipelines.
Our team has previously led large data science and machine learning teams (covering both applications and infrastructure), built startups, and created successful tools for enterprise ML.
We're backed by top AI investors, including Fei-Fei Li, Radical VC, and Costanoa VC.
We're looking for an experienced Backend Software Engineer to join as a founding team member of Delphina.
As one of our key early hires, you will partner closely with our early team on the direction of our product and drive critical technical decisions. You will have a broad impact over the technology, product, and our company's culture.
You will be responsible for:
Architecting, building, and deploying the systems and services underlying our platform.
Partnering with our cross functional team of scientists, researchers, and engineers to transform how machine learning is done.
Ensuring that our systems are reliable, secure, and worthy of our customers' trust.
Experience with leading and building production systems to deliver on major product initiatives.
Proficiency in at least one programming language commonly used within backend systems, e.g. Go, Python, Scala, or Java.
Energy and ambition to build a product that is surprisingly good in surprising ways.
Intrinsic desire to always be improving our product and yourself. Growth mindset to both stay ahead of the curve and pick up whatever knowledge you're missing to get the job done.
Experience with large-scale processing technologies and frameworks, such as Spark and Flink
Experience working directly on machine learning – either by partnering with scientists and engineers who are building models, or by building models yourself
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