
Job Overview
Location
San Francisco
Job Type
Full-time
Category
Operations
Date Posted
April 18, 2026
Full Job Description
đź“‹ Description
- • Strategic Projects Lead at SuperAnnotate, Inc. is a pivotal role responsible for driving high-impact, cross-functional initiatives that accelerate the company’s mission to power responsible AI through high-quality human data. This position sits at the intersection of operations, product, and strategy, ensuring that complex projects are delivered with precision, transparency, and scalability.
- • Day to day, the Strategic Projects Lead will own end-to-end project lifecycle management — from scoping and planning to execution and reporting — collaborating closely with engineering, data operations, sales, and executive teams to align resources, mitigate risks, and meet aggressive timelines. They will develop project frameworks, track key performance indicators, and communicate progress to stakeholders while continuously improving processes for efficiency and quality.
- • SuperAnnotate is a fast-growing Series B startup trusted by industry leaders like Databricks and ServiceNow, backed by NVIDIA, Dell Technologies Capital, and Lionel Messi’s Play Time VC. The company is the top-ranked AI data company on G2 for multiple consecutive years, including 2025, and operates a global network of expert specialists to deliver scalable, transparent data solutions for next-generation AI models.
- • In this role, the individual will develop deep expertise in AI data lifecycle management, strategic initiative execution, and scaling operations in a high-growth tech environment. They will gain visibility into executive decision-making, refine leadership and stakeholder management skills, and contribute directly to SuperAnnotate’s market leadership and innovation trajectory.
Skills & Technologies
About SuperAnnotate, Inc.
SuperAnnotate provides a data annotation and model training platform that combines AI-assisted labeling tools, project management workflows, and quality assurance features. Teams use the software to label images, video, text, LiDAR, and audio for computer-vision and NLP applications. The platform includes automation models, collaboration dashboards, analytics, and integrations with cloud storage and MLOps pipelines. Founded in 2018, the company serves enterprises and AI research groups that need scalable, high-accuracy training datasets.
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