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Software Engineer, Data Infrastructure

DatologyAIRedwood CityOnsite

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 an experienced Data Platform Engineer to join as a member of our core Datology AI team. As one of our early 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


  • Have meaningful experience with leading and building production data systems to deliver on major product initiatives.
  • You have built and managed highly scalable data processing solutions (e.g. Spark, Flink), data lakes or warehouses (e.g. Snowflake, Hive), authored queries (SQL), distributed storage systems (e.g., HDFS, S3), used workflow management (e.g. Airflow, Dagster), and have experience maintaining the infra that supports these.
  • Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
  • Expertise with any of ETL schedulers such as Airflow, Dagster, or similar frameworks.
  • Experience maintaining a high quality bar for design, correctness, and testing.
  • Take pride in building and operating scalable, reliable, secure systems
  • Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
  • Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done
  • You have experience being the technical lead of a Data Engineering / Platform / Infrastructure Team.
  • Experience building ML/DL systems and/or data infrastructure that feeds into training large ML models

Compensation


At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $180,000 to $250,000.

  • The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.

Life at DatologyAI

Thrive Here & What We Value1. Fastgrowing startup with a focus on innovation and growth | 2. Collaborative work environment where everyone is encouraged to contribute ideas and take ownership of their work | 3. Emphasis on worklife balance, with flexible hours and remote work options available | 4. Opportunities for professional development and career advancement within the company</s> | 1. Fastpaced and iterative environment | 2. Collaborative team culture | 3. Focus on quality, functionality, and human communication | 4. Humble attitude and eagerness to help colleagues | 5. Desire to do whatever it takes to make the team succeed</s> | 1. Collaborative and supportive work environment | 2. Emphasis on innovation and creativity | 3. Focus on customer satisfaction and success | 4. Opportunities for career growth and professional development | 5. Flexible work arrangements and worklife balance</s> | 1. Dedicated to rewarding talent with highly competitive salary and significant equity. | 2. Rapidly scaling team and computing resources to revolutionize data curation across modalities. | 3. Partnering closely with founders on the direction of our product and driving businesscritical technical decisions. | 4. Contributing to developing core products, starting from main data curation pipeline. | 5. Ensuring that systems are reliable, secure, and worthy of customers' trust.</s> | 1. Collaborative and supportive team environment | 2. Focus on innovation and staying ahead of industry trends | 3. Emphasis on worklife balance and flexibility | 5. Competitive salary and significant equity.</s> | 1. Collaborative environment where scientists work closely with engineers, talk to customers, and shape the product vision. | 2. Dedicated to rewarding talent with highly competitive salary and significant equity. | 3. Focus on realworld needs rather than conference reviewers and academic benchmarks. | 4. Emphasis on adaptability, communication, and collaboration skills in a startup environment.</s>

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