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. For more details, check out our recent blog posts sharing our high-level results for text models and image-text models.We've raised over $57M in funding from top investors like Radical Ventures, Amplify Partners, Felicis, Microsoft, Amazon, and notable angels like Jeff Dean, Geoff Hinton, Yann LeCun and Elad Gil. We're rapidly scaling our team and computing resources to revolutionize data curation across modalities.This role is based in Redwood City, CA. We are in office 4 days a week.
About the Role
We're looking for an experienced Infrastructure Engineer to join as a member of our core Datology AI team. As one of our early senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions. You will lead the development of our data infrastructure capabilities, including multi-cloud support and support for various deployment models, as well as training and inference infrastructure. You will have a broad impact on the technology, product, and our company's culture.
What You'll Work On
- Design and build the development and production platforms that power our products, enabling reliability and security at scale
- Architect, build, and deploy our core infrastructure while supporting multiple cloud providers and various deployment models
- Accelerate company productivity by empowering your fellow engineers & teammates with excellent tooling and systems, providing a best-in-case experience
- Partner with researchers and engineers to bring new features and research capabilities to our customers
About You
- Have meaningful experience in spearheading and constructing large-scale infrastructure
- Proficiency in bash, Kubernetes, Python, and/or Terraform or similar technologies
- Have experience working with AWS, other cloud platforms such as Azure or GCP and/or on-prem environments
- Have expertise in debugging problems across the stack, such as networking issues, performance problems, hardware issues or memory leaks
- Take pride in building and operating scalable, reliable, secure systems
- Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
- Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done
We would love it if you had:
- Built out data infrastructure from, or nearly from, scratch at a fast-growing startup.
- Experience building ML/DL infrastructure and/or data infrastructure that feeds into training large ML models
Compensation
At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $180,000 to $250,000.
- The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
