Edtech.com's Summary

HackerRank is hiring an AI Data Operations Manager. The role involves managing the complete lifecycle of data processing, from raw content to creating well-labeled datasets for machine learning models. The manager will work closely with ML researchers, product teams, and a network of subject-matter-expert (SME) labelers to deliver production-ready datasets to both internal stakeholders and customers.

Highlights

Manage end-to-end data pipeline for machine learning and LLMs.
Gather data requirements and coordinate global labelers.
Design scalable workflows and run quality control processes.
4+ years experience in data operations for ML, NLP, and AI projects.
Proficiency with SQL or Python/pandas and project management skills.
Base salary range: $130,000 to $150,000.
Experience with ML/LLM data formats and annotation platforms.

AI Data Operations Manager Full Description

At HackerRank, we are on a mission to change the world to value skills over pedigree. We are a high-performing, mission-driven team that truly, madly, deeply cares about what we do. We don’t see velocity and quality as tradeoffs; both matter. If you take pride in high-impact work and thrive in a driven team, HackerRank is where you belong.

About the team:

HackerRank’s Machine Learning team is working on the cutting edge of AI. We’re actively researching and building solutions for a number of exciting initiatives, including plagiarism detection within our Integrity Workstream, how LLMs perform across the SDLC via our ASTRA evaluation harness and benchmark, the types of datasets that can further improve LLMs on software engineering tasks, and finally how far we can take software development agents with our rich datasets.

About the role:

The AI Data Operations Manager owns the end-to-end pipeline that turns raw content into clean, well-labeled datasets for training and evaluating machine-learning models and LLMs. You’ll gather data requirements from ML researchers and product teams, work with our Content team to coordinate a global network of subject-matter-expert (SME) labelers, and deliver production-ready datasets to internal stakeholders and customers.

What you'll do:

Requirement gathering – Translate model or product needs into clear data specs, timelines, and success metrics.
Labeler & vendor management – Source, onboard, and coach SME labelers or third-party vendors; track throughput and cost.
Process & quality control – Design scalable workflows, run sampling audits, and drive continual quality improvements (e.g., inter-annotator agreement targets).
Data delivery & documentation – Package datasets with schemas, metadata, and usage guidelines; ensure security and licensing compliance.

You will thrive in this role if you:

Understand the importance of operational excellence, strong organizational skills, and the ability to drive multiple stakeholders who are all going to be busy and distracted.
Can handle ambiguity and drive clarity.
Can strike the right balance between customer requests and internal requests.
Are able to quickly identify and troubleshoot bottlenecks in complex and human-driven processes at scale.

What you bring:

4+ years in data operations, program management, or content operations for ML, NLP, and AI projects.
Hands-on experience shipping labeled datasets at scale and running quality-control processes, determining the best balance between building and buying tools to scale.
Working knowledge of ML/LLM data formats and annotation platforms (e.g., Labelbox, Scale, custom tools).
Strong project-management skills and proficiency with SQL or Python/pandas for metric tracking.
Excellent written and verbal communication; able to work with engineers, researchers, and customers.

Bonus Skills:

Experience with coding challenges or software engineering datasets.
Familiarity with privacy and security frameworks (GDPR, SOC 2).
Record of managing distributed or crowdsourced labeling teams.

Current base salary range: ($130,000 to $150,000). The exact salary may vary based on skills, experience, location, market ranges, and other compensation offered. The salary range does not include other compensation components, commissions (for sales-related roles), bonuses, or benefits that you may be eligible for. Salary may be adjusted based on business needs.

Want to learn more about HackerRank? Check out HackerRank.com to explore our products, solutions and resources, and dive into our story and mission here.

HackerRank is a proud equal employment opportunity and affirmative action employer. We provide equal opportunity to everyone for employment based on individual performance and qualification. We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

Notice to prospective HackerRank job applicants:

Our Recruiters use @hackerrank.com email addresses.
We never ask for payment or credit check information to apply, interview, or work here.

Original Job Description

About the team:

About the role:

What you'll do:

Requirement gathering – Translate model or product needs into clear data specs, timelines, and success metrics.
Labeler & vendor management – Source, onboard, and coach SME labelers or third-party vendors; track throughput and cost.
Process & quality control – Design scalable workflows, run sampling audits, and drive continual quality improvements (e.g., inter-annotator agreement targets).
Data delivery & documentation – Package datasets with schemas, metadata, and usage guidelines; ensure security and licensing compliance.

You will thrive in this role if you:

Understand the importance of operational excellence, strong organizational skills, and the ability to drive multiple stakeholders who are all going to be busy and distracted.
Can handle ambiguity and drive clarity.
Can strike the right balance between customer requests and internal requests.
Are able to quickly identify and troubleshoot bottlenecks in complex and human-driven processes at scale.

What you bring:

4+ years in data operations, program management, or content operations for ML, NLP, and AI projects.
Hands-on experience shipping labeled datasets at scale and running quality-control processes, determining the best balance between building and buying tools to scale.
Working knowledge of ML/LLM data formats and annotation platforms (e.g., Labelbox, Scale, custom tools).
Strong project-management skills and proficiency with SQL or Python/pandas for metric tracking.
Excellent written and verbal communication; able to work with engineers, researchers, and customers.

Bonus Skills:

Experience with coding challenges or software engineering datasets.
Familiarity with privacy and security frameworks (GDPR, SOC 2).
Record of managing distributed or crowdsourced labeling teams.

Want to learn more about HackerRank? Check out HackerRank.com to explore our products, solutions and resources, and dive into our story and mission here.

Notice to prospective HackerRank job applicants:

Our Recruiters use @hackerrank.com email addresses.
We never ask for payment or credit check information to apply, interview, or work here.

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Edtech.com's Summary

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