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Data Annotation Education So Jobs (NOW HIRING)

Human Data Architect, Quality

New York, NY · On-site

$130K - $160K/yr

... so the standard is enforceable at scale. Who You Are Required Background * 5+ years working at the intersection of ML and data - annotation methodology, dataset curation, data-centric ML, ground ...

Senior EKG Analyst

CA · Remote

$27 - $30/hr

... rhythm interpretation, annotation, and quality-focused analysis of cardiac data to support ... education and experience. The range is a good faith estimate and may be modified in the future.

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Data Annotation Education So information

What is the difference between Data Annotation Education So vs Data Labeler?

AspectData Annotation Education SoData Labeler
Required CredentialsTypically requires training in annotation tools and basic data handlingUsually requires minimal formal education, focus on task-specific instructions
Work EnvironmentOften in training or educational settings, sometimes remotePrimarily in data labeling tasks, often remote or on-site
Industry UsageUsed in educational programs, training for data annotation rolesCommonly employed in data annotation and machine learning projects

Data Annotation Education So focuses on training individuals in data annotation techniques, often within educational or training contexts. In contrast, Data Labeler is a role that involves performing data labeling tasks in real-world projects. While both roles involve data annotation, the former emphasizes education and skill development, whereas the latter is about executing labeling tasks for AI and machine learning models.

Infographic showing various Data Annotation Education So job openings in the United States as of May 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 50% In-person, and 50% Remote job distribution.
Software Engineer, ML Data Infrastructure

Software Engineer, ML Data Infrastructure

Nuro

Mountain View, CA

$160K - $240K/yr

Full-time

Posted 4 days ago


Job description

Who We Are

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world's most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.

About the Role

Nuro takes a machine-learning-first approach to autonomous driving technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data.

The team plays a crucial role in the advancement of autonomous driving systems by creating a scalable and reliable data infrastructure. This infrastructure is designed to produce training and evaluation data derived from both on-road collected logs and simulation logs. Additionally, the team collaborates closely with system engineers to thoroughly validate the autonomous driving system before its deployment.

About the Work

  • Design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation.
  • Create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics.
  • Construct intuitive dashboards and reports to present evaluation results, facilitating straightforward comparisons that highlight both improvements and regressions of the ML components and the overall system.
  • Develop and maintain continuous testing and monitoring systems to guarantee the integrity and resilience of our data and associated data pipelines.
  • Develop data mining tools with applied ML techniques to support data discovery needs from Autonomy including Perception, Behavior, and Mapping
  • Develop data annotation tools to support first-party and third-party labeling workforce to provide high fidelity perception, mapping, and driving trajectory labels
  • Scale data annotation labels with applied State-of-the-art ML techniques

About You

  • You have a degree in BS, MS.c or Ph.D, plus 1+ years of relevant work experience
  • Strong proficiency in Python or similar languages
  • Domain experience: Experience working with large-scale data and building scalable & reliable systems/data pipelines; ability to understand and design complex systems
  • Technical excellence: Ability and willingness to deep dive into implementation, driving technical standards and best practices across broader software organization
  • A bachelor's degree in Computer Science, Electrical Engineering, or a closely related field

Bonus Points

  • Strong proficiency in C++ or other high-performance low-level languages
  • Strong knowledge of GCP, GCS, BigQuery, or PostgreSQL
  • Knowledge of data engineering, and its tooling and best practices
  • Knowledge of batch and streaming data processing, warehousing, and analytics solutions
  • Experience working with large-scale distributed data systems
  • Experience with system & framework design
  • Experience with data workflow orchestration platforms

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.