.png)
The quality of data underpins Generative AI programs. At Scale, Quality Control is responsible for ensuring data we deliver to the world’s leading AI customers is state of the art.
As a Quality Operations Lead, you’ll own that call for some of our highest-impact Generative AI programs. You'll lead a large team of quality control specialists to measure and improve quality across these programs, from multilingual post-training data to agentic RL environments. You will work on frontier-level problems – the programs you work on train the models people are talking about.
You will hold delivery teams accountable across our highest-impact projects – helping solve nuanced quality issues, as well as leading strategic initiatives to enable reliable, scalable operations across the organization.
What you’ll do
- Lead and grow a team of quality specialists - hire, coach and calibrate this team of specialists.
- Turn unclear customer requirements into clear standards - work with delivery teams to interpret and improve customer requirements, and then turn that into measurable signals of data quality.
- Run the quality system. Own the daily operation: plan and allocate workforce capacity, produce quality reporting, measure productivity and efficiency, and drive quality control policies.
- Analyzing quality trends. Identify, root-cause, and elevate defect patterns that delivery teams can take action on.
- Build the future of QC. Our team already leverages agentic capabilities, but you will help decide and lead what gets built next to continue to scale and optimize our quality operations.
Ideally you’d have
- A Bachelor’s degree in Computer Science, Engineering, Operations, or a related field.
- 3+ years leading teams or scaling large operational/technical processes.
- Strong analytical and problem-solving skills (particularly in SQL) with attention to detail.
- Experience building systems, processes, and teams across multiple customer segments or product lines.
- A hands-on background in product management, operations management, program management, or top-tier management consulting.
- Proven experience taking initiative in cross-functional technical environments.
Nice to haves:
- Master’s degree in Computer Science, Engineering, Operations, or a related field.
- Experience in AI/ML services, data annotation or model evaluation.
- Experience in a fast-growing, less-structured startup environment.
- Experience building teams from the ground up.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
