Software Engineer Intern, Infrastructure en DatologyAI

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 a Software Engineer Intern to join our Infrastructure team at DatologyAI. You’ll work closely with experienced engineers to design and build the systems that power large-scale data curation and model training. This is an opportunity to learn how cutting-edge AI infrastructure is built from the ground up—across distributed systems, multi-cloud environments, and high-performance compute platforms.

As an intern, you’ll take ownership of meaningful projects that contribute directly to our production systems and internal tooling. You’ll learn how to think about scale, reliability, and efficiency in the context of modern AI workloads, while collaborating with some of the strongest engineers and researchers in the field.

What You'll Work On

• Build and improve internal tools that accelerate developer productivity and system reliability

• Design and prototype components of DatologyAI’s distributed training and data infrastructure

• Contribute to automation, deployment, and observability systems across multi-cloud and on-prem environments

• Collaborate with engineers and researchers to bring new ML infrastructure capabilities to production

• Participate in code reviews, technical discussions, and learn best practices for scalable infrastructure development

About You

• Pursuing a BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field

• Strong programming skills in Python, Go, or C++

• Familiar with Linux systems, Docker, Kubernetes, or similar technologies

• Curious about cloud computing (AWS, Azure, or GCP) and large-scale distributed systems

• Excited to learn how infrastructure enables ML research and model deployment at scale

• Collaborative, detail-oriented, and eager to take on complex technical problems

Compensation

This is a paid internship with a standard monthly stipend. If you are not currently located in the Bay Area, we provide a relocation stipend to help cover travel and living expenses during your three months on-site.

We 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 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.