Scale AI is seeking an experienced Head of Frontier Data Operations to spearhead our most advanced AI projects, including AI agents, audio, and model evaluation. This leadership role is essential in driving innovation, overseeing the development of new datasets, and managing teams focused on the latest advancements in AI technology. The Head of Frontier Data Ops will play a crucial role in shaping our AI initiatives, ensuring the highest standards of quality, and fostering a culture of excellence and collaboration.
You will:Be a Leader
- Drive the development and execution of high-impact projects in AI agents, speech recognition, and model evaluation.
- Provide strategic direction and oversight to ensure projects align with Scale AI’s goals and industry advancements.
- Collaborate with research and engineering teams to integrate cutting-edge AI models with robust data development practices.
- Manage and mentor specialized teams, including Strategic Project Leads (SPLs) and Single Threaded Owners (STOs), fostering a high-performance culture.
- Encourage innovation, continuous improvement, and professional growth within the team.
- Ensure effective collaboration and communication across cross-functional teams and departments.
Build data strategy and tooling roadmap
- Formulate and implement comprehensive data development strategies tailored to frontier AI applications.
- Oversee data collection, annotation, and validation processes to ensure high-quality datasets.
- Stay informed about the latest AI trends and technologies to drive strategic initiatives and maintain competitive edge.
- Identify opportunities for enhancing data development workflows through innovative tools and products.
- Lead the design, development, and deployment of solutions that improve data collection, annotation efficiency, and overall data quality.
- Collaborate with IT and development teams to ensure seamless integration of new tools into existing systems.
Handle Quality assurance & model improvement
- Oversee the establishment of robust evaluation metrics and benchmarks for AI models.
- Work closely with research teams to assess model performance, identify strengths and areas for improvement, and ensure models meet desired standards.
- Implement and maintain rigorous quality assurance processes to uphold data integrity and reliability.
- Coordinate with Quality Assurance (QA) teams to monitor data quality and address any issues promptly and effectively.
Champion collaboration & communication
- Facilitate collaboration between research scientists, engineers, product managers, and other stakeholders to drive cohesive project outcomes.
- Promote knowledge sharing and best practices across different teams and projects.
- Communicate project goals, progress updates, and outcomes to executive leadership and key stakeholders.
- Prepare and deliver reports and presentations that highlight project achievements, challenges, and strategic plans.
Talent development
- Cultivate a positive and inclusive work environment that promotes team engagement and retention.
- Implement initiatives to boost team morale, encourage collaboration, and support professional development.
Ideally, you’d have:Experience & education
- Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 7-10 years of experience in AI, machine learning, or data science roles.
- Proven track record in leading data development projects for AI applications.
- Expertise in AI agents, speech recognition systems, and model evaluation methodologies.
Skills & competencies
- Deep understanding of machine learning algorithms, data annotation techniques, and AI model evaluation.
- Proficiency in programming languages such as Python and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).
- Strong leadership abilities with experience managing cross-functional and high-performing teams.
- Excellent project management skills, capable of overseeing multiple complex projects simultaneously.
- Ability to analyze complex data and make data-driven decisions.
- Strategic mindset with a focus on innovation and long-term planning.
- Exceptional verbal and written communication skills.
- Ability to convey complex technical concepts to non-technical stakeholders effectively.
Personal Attributes
- Passionate about advancing the field of AI and exploring new frontiers.
- Creative thinker who can develop novel solutions to complex problems.
- Strong team player who values diverse perspectives and fosters collaboration.
- Comfortable working in a fast-paced, dynamic environment with evolving priorities.
This Role Is Critical For:
- Driving the development of high-quality datasets essential for training and evaluating cutting-edge AI models.
- Leading initiatives that push the boundaries of AI agents, speech recognition, and model evaluation technologies.
- Contributing to Scale AI's strategic objectives by ensuring successful and impactful frontier AI projects.
- Building and nurturing high-performing teams that are motivated, skilled, and aligned with the company's vision.
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, determined by work location and additional factors, including job-related skills, experience, 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 reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$195,000—$245,000 USD
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, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. 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 accommodations@scale.com. 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.
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Top Skills
What We Do
Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.
