MTS, Machine Learning Engineer

About Delphina

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.

What you’ll do

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.

What we’re looking for

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.

Nice to haves

Experience building + shipping ML production systems

Experience with data management and distributed data processing solutions (e.g. Spark, Snowflake, etc.)

Benefits

Equity in the company

Medical, dental, and vision insurance

401k

Unlimited PTO

Top of the line Apple equipment

Free lunch in the office