Software Engineer, Data Infrastructure

ABOUT THE COMPANY Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. 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 Data Platform Engineer to join as a member of our core Engineering team. As one of our 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 core product and data platform. These are key components of our stack that allow us to process customer data and apply state of the art research for identifying the most informative data points in large-scale datasets. You will have a broad impact over the technology, product, and our company's culture. We provide visa sponsorship for candidates selected for this role. WHAT YOU'LL WORK ON - Design, build and maintain highly scalable data processing solutions, while ensuring scalability, reliability, and security - Architect, build, and deploy the back-end systems and services that power our data curation platform - Partner with researchers and engineers to bring new features and research capabilities to our customers - Ensure that our systems are reliable, secure, and worthy of our customers' trust ABOUT YOU - 4+ years of experience in data engineering, including owning production systems end-to-end -- scalable processing (Spark, Flink), storage (HDFS, S3), lakes/warehouses (Snowflake, Hive), SQL, and workflow orchestration (Airflow, Dagster). - Proficiency in Python, Scala, or Java. - Experience as a technical lead of a Data Engineering, Platform, or Infrastructure team. - Experience building ML/DL systems or data infrastructure that feeds large-scale model training. - High bar for design, correctness, and testing. You build systems that are scalable, reliable, and secure. - Low ego, high ownership. You help your teammates, pick up whatever's needed, and see problems through to completion. Don’t meet every single requirement? We still encourage you to apply. If you’re excited about our mission and eager to learn, we want to hear from you! COMPENSATION At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000. - Starting pay is based on job-related skills, experienc