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 a Machine Learning Engineer to join as a Member of our Technical Staff at Delphina
As one of our key hires, you will partner closely with our team on the direction of our product and drive critical technical decisions. You will have broad impact over the technology, product, and our company's culture.
As an MLE at Delphina, you will conduct research investigating how ML workflows can be automated. You will be responsible for:
Making sense of existing research and transforming the latest academic research and best practices into production-ready solutions. You will use your skills as a scientist to source, vet, implement, and improve promising ideas from both the research literature and of your own creation.
Partnering closely with customers. It's both critical that our early customers are successful in using the Delphina product, and also that you are an expert in what customers really need.
Turning science and customer needs into product. Our MLEs are deep in the code directly, and collaboratively closely with the rest of our cross functional team to shape our direction and drive outcomes.
Working independently. We believe that scientists benefit from high levels of autonomy and we are indexed on giving you the space you need to succeed.
We are looking for practical experience in the following areas:
Feature engineering and feature search
Tree-based models and deep learning
Timeseries modeling
Production ML uses-cases in areas including fintech and manufacturing
LLM Agents
AutoML
Sufficient software engineering skills to conduct large-scale research experiments and build production prototypes
Demonstrated track record of success
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 building + shipping ML production systems
Experience with data management and distributed data processing solutions (e.g. Spark, Snowflake, etc.)
Equity in the company
Medical, dental, and vision insurance
401k
Unlimited PTO
Top of the line Apple equipment
Free lunch in the office
