- Location
- Redwood City, California, USA
- Employment
- Full time
- Level
- Mid level
- Posted
- 31 months ago
About this role
About the Company
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. 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. For more details, check out our recent research on synthetic data scaling (BeyondWeb) and pretraining with domain-specific data (The Finetuner’s Fallacy).
We raised a total of $57.5M in two rounds, a Seed and Series A. 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.
This role is based in Redwood City, CA. We are in office 4 days a week.
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. 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. This role requires strong scientific judgment, fluency with the deep learning literature, and the drive to work autonomously in a fast-moving startup environment.
What You'll Work On
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.
Our research is guided by concrete customer needs and product outcomes, not conference benchmarks. You'll have clear context on why your work matters and who it serves.
How You'll Work
We believe researchers do their best work with autonomy. You'll have the freedom to pursue problems in the way that works best for you, with the resources and context to back it up.
We expect Research Scientists to collaborate closely with engineers, talk to customers, and shape the product vision.
About You
3+ years of deep learning research experience
Strong fundamentals in deep learning
Practical experience and/or publications in one or more of the following areas:
Data pruning and curation
Curriculum learning
Synthetic data generation
Dataset distillation
Effects of training data on model behavior
Embedding models and semantic search
Training large vision (including video), language, or multimodal models
Efficient ML
Enough software engineering and PyTorch experience (or willingness to learn) to run large-scale experiments and build production prototypes
A demonstrated track record in deep learning research, whether through papers, tools, or other artifacts
Nice to have:
Experience with distributed data processing tools like Spark or Snowflake
Experience building and shipping ML products
Candidates do not need a PhD or extensive publications. Some of the best researchers we've worked with have no formal training in machine learning, and obtained all of their experience working in industry and building products. We believe adaptability, combined with exceptional communication and collaboration skills, are the most important ingredients for successful research in a startup environment.
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.
Our benefits are built to support your well-being and growth:
100% covered health benefits (medical, vision, and dental).
401(k) plan with a generous 4% company match.
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.
Daily lunches and snacks are provided in our office!
Relocation assistance for employees moving to the Bay Area.
As published by DatologyAI. Applications are handled on their site.
Skills this posting mentions
About DatologyAI
DatologyAI builds tools to automatically select the best data on which to train deep learning models. Our tools leverage cutting-edge research - much of which we perform ourselves - to identify redundant, noisy, or otherwise harmful data points. The algorithms that power our tools are modality-agnostic - they’re not limited to text or images - and don’t require labels, making them ideal for realizing the next generation of large deep learning models. Our products allow customers in nearly any vertical to train better models for cheaper.
All 15 openings at DatologyAIOne click, then it is written
Apply to DatologyAI with a resume written for this role.
Queue Research Scientist and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in DatologyAI’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
Listed from the job board DatologyAI publishes. Refolk is not the employer and does not handle their hiring. Applications go to DatologyAI directly.