Demo

Research Engineer

DatologyAI
Redwood, CA Full Time
POSTED ON 2/28/2025
AVAILABLE BEFORE 5/25/2025

About the Company

Companies want to train their own large models on their own data. The current industry standard is to train on a random sample of your data, which is inefficient at best and actively harmful to model quality at worst. There is compelling research showing that smarter data selection can train better models faster-we know because we did much of this research. Given the high costs of training, this presents a huge market opportunity. We founded DatologyAI to translate this research into tools that enable enterprise customers to identify the right data on which to train, resulting in better models for cheaper. Our team has pioneered deep learning data research, built startups, and created tools for enterprise ML.

Following our $11.65M Seed round last September, we've raised a $46M Series A led by Felicis Ventures. Our investors include Radical Ventures, Amplify Partners, Microsoft, Amazon, and notable angels like Jeff Dean, Geoff Hinton, Yann LeCun and Elad Gil. With over $57.5M in total funding, we're rapidly scaling our team and computing resources to revolutionize data curation across modalities.

Join us in pushing the boundaries of what's possible in AI! Learn more about the company here.

About the Role

As a Research Engineer, you will play a crucial role in conducting and enabling cutting-edge research and translating it into our core product pipeline. You will work closely with other members of the technical staff to develop and improve state-of-the-art data curation strategies. Your technical skills will accelerate our research and ensure that our product remains at the forefront of innovation.

About You

There are a few specific things we'll be looking for that will help you succeed in this role :

  • Bachelor's degree or equivalent practical experience.
  • 3-4 years of experience in an industry research lab or equivalent academic experience.
  • Strong background in machine learning systems, such as distributed training of large models and / or ML performance optimization.
  • Knowledge of ML / AI applications and models, especially foundation models, how they are constructed, and how they are used.
  • Experience contributing to research communities, including open-source research projects or publishing at conferences (e.g., CVPR, NeurIPS, ICCV / ECCV, BMVC).
  • Strong foundations in software engineering and empirical research.
  • Ability to work separately and as part of a team. Excellent communication and presentation skills.

We would love it if candidates have :

  • PhD in Computer Science with an emphasis on Machine Learning, or a related technical field.
  • Experience working in an industry or academic research lab, focusing on multiple aspects of the research to product pipeline.
  • Compensation and Benefits

    At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $150,000 to $250,000.

  • The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
  • We also offer a comprehensive benefits package to support our employees' well-being and professional growth :

  • 100% covered health benefits (medical, vision, and dental).
  • 401(k) plan with a generous 4% company match.
  • Unlimited paid time off (PTO) policy.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Daily lunches and snacks are provided in our office!
  • Relocation assistance for employees moving to the Bay Area.
  • Salary : $150,000 - $250,000

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    Job openings at DatologyAI

    DatologyAI
    Hired Organization Address Redwood, CA Full Time
    About the Company Companies want to train their own large models on their own data. The current industry standard is to ...
    DatologyAI
    Hired Organization Address Redwood, CA Full Time
    About the Company Companies want to train their own large models on their own data. The current industry standard is to ...

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