Datology AI

Datology AI

Research Scientist

Redwood City

Sponsorship not specified$180k-$300kDetected 92 days ago
SnowflakeMachine LearningDeep LearningPyTorchSparkData EngineeringResearchCommunicationCollaborationAdaptability

About the role

  • We're looking for a Research Scientist to investigate how intervening on training data can improve the quality and shape the behavior of deep learning models.
  • The research literature is vast, rife with ambiguity, and constantly evolving.
  • Our research is guided by concrete customer needs and product outcomes, not conference benchmarks.

Responsibilities

  • You'll source and implement ideas from the literature, conduct research grounded in real customer needs, and collaborate closely with engineers and product teams to turn findings into tangible impact.
  • The research literature is vast, rife with ambiguity, and constantly evolving. You'll source, vet, implement, and improve promising ideas from the literature and your own thinking.
  • Enough software engineering and PyTorch experience (or willingness to learn) to run large-scale experiments and build production prototypes

Nice to have

  • Experience with distributed data processing tools like Spark or Snowflake
  • Candidates do not need a PhD or extensive publications.
  • We believe adaptability, combined with exceptional communication and collaboration skills, are the most important ingredients for successful research in a startup environment.
  • Starting pay is based on job-related skills, experience, qualifications, and interview performance.
  • 401(k) plan with a generous 4% company match.
  • Daily lunches and snacks are provided in our office!
  • Relocation assistance for employees moving to the Bay Area.

Skills

  • A demonstrated track record in deep learning research, whether through papers, tools, or other artifacts

Compensation

  • At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000.
  • Starting pay is based on job-related skills, experience, qualifications, and interview performance.
  • 401(k) plan with a generous 4% company match.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Daily lunches and snacks are provided in our office!

Benefits

  • 100% covered health benefits (medical, vision, and dental).
  • Unlimited PTO policy
  • Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Curriculum learning

Company info

  • Models are what they eat.
  • But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
  • At DatologyAI, we've built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models.
  • For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner's Fallacy https://www.datologyai.com/blog/finetuners-fallacy).
  • We raised a total of $57.5M in two rounds, a Seed and Series A.
  • This role is based in Redwood City, CA.
  • We are in office 4 days a week.
  • Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment.
  • Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models.
  • Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
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This listing is sourced directly from Datology AI's careers page and normalized into a canonical job model.