Software Engineer, Infrastructure
DatologyAI1 month ago
San Mateo, CA, USASenior
Base Salary
$180k - $300k/yr
Responsibilities
- Design and build development and production platforms that provide reliability and security at scale.
- Architect, build, and deploy core infrastructure across multiple cloud providers and deployment models.
- Develop tooling and systems that improve engineering and company productivity.
- Partner with researchers and engineers to deliver product features and research capabilities.
- Support data infrastructure as well as training and inference infrastructure.
Requirements
- At least 4 years of relevant experience.
- Meaningful experience spearheading and constructing large-scale infrastructure.
- Proficiency in Bash, Kubernetes, Python, and Terraform or similar technologies.
- Experience with AWS, Azure, GCP, or on-premises environments.
- Expertise debugging networking, performance, hardware, memory, and other cross-stack issues.
- Ability to build and operate scalable, reliable, and secure systems.
- Preferred experience building data infrastructure from or nearly from scratch at a fast-growing startup.
- Preferred experience building ML/DL infrastructure or data infrastructure supporting large ML model training.
Benefits
- 100% covered medical, vision, and dental benefits.
- 401(k) plan with a 4% company match.
- Unlimited paid time off.
- 12 weeks of paid parental leave plus six months of work-from-home flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily office lunches and snacks.
- Relocation assistance for employees moving to the Bay Area.
- Based in San Mateo, California, with four days per week in the office.
Tech Stack
Categories
About DatologyAI
DatologyAI builds software that automatically curates and selects training data for deep learning, removing redundant or harmful examples across text, image, and other modalities. Its data-curation suite helps ML teams train better models with fewer labels and lower compute by optimizing large, unlabeled datasets. Founded in 2023 and headquartered in Redwood City, California, the privately held company sells its tools to organizations building large-scale AI systems across industries.