Research Engineer
DatologyAI5 months ago
San Mateo, CA, USAMid Level
Base Salary
$180k - $300k/yr
Responsibilities
- Build and scale reliable, fast, and cost-efficient data processing and curation pipelines for massive language, vision, and multimodal datasets.
- Design experimentation infrastructure that enables researchers to run large-scale experiments quickly.
- Translate research results into production-grade systems used by customers.
- Profile and optimize large-scale training and data workloads across frontier-scale compute environments.
- Collaborate substantively with researchers and technical staff on state-of-the-art data curation strategies.
Requirements
- Have 3+ years of experience building ML systems, data infrastructure, or large-scale distributed applications.
- Demonstrate strong software engineering fundamentals and fluency in Python.
- Have hands-on experience with PyTorch.
- Have experience with distributed data processing and/or distributed training using tools such as Spark, Ray, Dask, or Snowflake.
- Be comfortable operating large-scale compute, including GPU clusters and cloud infrastructure.
- Have sufficient machine learning depth to collaborate substantively with researchers.
- Show a track record of shipping systems others rely on through production infrastructure, open-source tools, or other artifacts.
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 lunches and snacks provided in the office.
- Relocation assistance for employees moving to the Bay Area.
- Based in San Mateo, CA, with in-office work four days per week.
Tech Stack
Categories
Data EngineeringML 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.