Software Engineer, Data Infrastructure
DatologyAIover 1 year ago
Base Salary
$180k - $300k/yr
Responsibilities
- Design, build, and maintain highly scalable data processing solutions with strong scalability, reliability, and security.
- Architect, build, and deploy backend systems and services powering the data curation platform.
- Partner with researchers and engineers to bring new features and research capabilities to customers.
- Lead development of the core product and data platform and drive business-critical technical decisions.
- Own production systems end-to-end and contribute to reliable, secure, and well-tested infrastructure.
Requirements
- 4+ years of data engineering experience, including end-to-end ownership of production systems.
- Experience with scalable processing technologies including Spark and Flink; storage systems including HDFS and S3; lakes and warehouses including Snowflake and Hive; SQL; and workflow orchestration with Airflow or Dagster.
- Proficiency in Python, Scala, or Java.
- Experience serving as a technical lead for a data engineering, platform, or infrastructure team.
- Experience building ML/DL systems or data infrastructure that supports large-scale model training.
- Strong focus on design, correctness, testing, scalability, reliability, and security.
Benefits
- Company-provided medical, vision, and dental benefits are fully covered.
- 401(k) plan with a 4% company match.
- Unlimited paid time off.
- Twelve 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.
- Role is based in San Mateo, California, with four days per week in the office.
Tech Stack
Categories
BackendData Engineering
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.