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Senior ML Research Scientist

Galileo Financial Technologies
San Francisco, CA
Full-time

About Galileo

Galileo is a late-stage Series A business, founded in 2021 by Engineering Leaders from Google AI and Uber AI. The founders spent over 10 years building cutting edge Machine Learning systems at Google, Uber and Apple, and founded the company from the battle scars around building some of the biggest ML Platforms on the planet.

The big lesson learnt was that a Machine Learning model is only as good as the data you give it.

In the era of Generative AI and LLMs, the tools that Data Scientists use to do evaluations of Language Models and Applications includes ad-hoc python scripts, Jupyter Notebooks and Excel sheets.

This calls for new tools in the LLM development stack to mitigate data errors and biases, investigate regions of LLM underperformance, and help create high quality LLM based applications quickly via robust evaluation and experimentation tooling.

At Galileo, we are building a next generation Large Language Model (LLM) evaluation and experimentation platform to address this problem.

With dozens of paying enterprise customers across the enterprise and high growth startups, Galileo is creating the "LLM Evaluation" market.

Backed by tier 1 investors such as Battery Ventures and Walden Catalyst and over $23M in funding, Galileo is poised to build an enduring business centered around the core ingredient of machine learning - the data.

Role Description

We are looking for a Senior Machine Learning Research Scientist to join our team of top ML researchers and work with them in formulating advanced techniques and algorithms to aid a user in creating better datasets for ML.

Main Responsibilities

  • Work with top Machine Learning researchers in creating advanced ML algorithms in Large Language Modeling.
  • Build advanced ML algorithms around Language Models, in particular techniques to better surface errors and biases in modern day LLMs.
  • Collaborate with engineering and product management to understand use cases
  • Read and research the latest LLM evaluation literature and apply them to Galileo's product offerings
  • Work with Platform Engineering and Frontend teams, to ensure efficient computation times and robust delivery of robust ML algorithms from research to solve for the user's needs
  • Mentor other team members

Minimum Qualifications

  • 5+ years of experience in ML Research, exploring new model architectures and ML algorithms from scratch
  • Strong experience with Pytorch, TensorFlow, Keras, or other Deep Learning frameworks
  • Strong Experience with Generative or Seq-2-Seq Models
  • Strong understanding of data quality metrics, and advanced evaluation techniques in Machine Learning
  • Strong Python programming skills. Write efficient, clean, and scalable code.
  • Strong communication skills, ability to understand complex technical concepts.
  • Strong Research report writing skills
  • Strong ML problem-solving skills, ability to do independent experiments (a self-starter mindset), but also collaborate in a team environment

If you are passionate about Machine Learning and have experience in being a Tech Lead in an ML team, this is a great opportunity for you.

You will get to work on a groundbreaking product poised to revolutionize the way companies approach LLM Evaluations. Join our team at Galileo and help us build the future of Evaluations in Generative AI.

Why Galileo

  • Join a seasoned founding team that has previously led product and engineering teams from 0 to $100M+ in revenue and from 0 to 1B+ users globally
  • We obsess over our team's culture driven by inclusivity, empathy and curiosity
  • We invest in our team's development and happiness because our employees are the keys to our success and ensuring happy customers - towards that end, we offer :
  • Unlimited PTO
  • Parental leave - 100% pay for 8 weeks
  • Medical, Dental and Vision Insurance
  • 401 (K) Retirement Savings Plan
  • Early stage equity
  • Mental and Physical Wellness Stipend
  • Daily Lunch Stipend
  • 1 day ago
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