Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Leads technical and writing teams delivering generative AI products. Coordinates customers, data, product, and research teams; tracks annotator metrics; creates prompts and responses; manages labeling initiatives; develops guidelines; trains stakeholders on LLM and dataset best practices; and supports quality assurance while handling potentially sensitive content.

Develop and maintain prompts, responses, and datasets for large language models. Lead labeling initiatives with internal teams and third-party firms, create stakeholder guidelines, and train teams on LLM and dataset development best practices. The role requires native-level English, bilingual proficiency in an additional language, specialized domain knowledge, and a college degree or equivalent experience.

Reviews and scores robotics data episodes using standardized quality rubrics. Identifies failures, unsafe behavior, edge cases, and recurring quality trends; documents findings and provides actionable feedback. Collaborates with stakeholders and teleoperators to improve review workflows, standards, training, and documentation while meeting throughput and accuracy targets.

Annotate and manage training/test datasets, run model training, evaluate model performance, perform manual QA and error analysis, and refine annotation guidelines for NLP/ML projects.

Proofread and edit localized content for grammar, syntax, punctuation, consistency, and formatting issues. Translate occasional English content, test web applications and user interfaces on Mac OS X and iOS, document localization bugs, and verify fixes. Execute test cases, clearly communicate reproduction steps, prioritize issues, and collaborate independently or with diverse teams in a fast-paced environment, including occasional non-business hours, weekends, and holidays.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

Leads technical and writing teams delivering generative AI products, coordinating customers, data, product, and research teams. Tracks annotator metrics, manages labeling initiatives, creates prompts and responses, develops stakeholder guidelines, and trains teams on LLM and dataset best practices. The role includes customer interaction, quality assurance, and exposure to potentially toxic or sensitive content.

Leads localization testing engagements from scope estimation and environment setup through tester training, test execution, defect management, reporting, and sign-off. Coordinates with translation teams, engineers, project managers, testers, and clients to investigate and resolve defects, prevent duplicates, monitor progress, maintain testing equipment, and deliver quality results. Evaluates tester performance and supports the ongoing maturity of testing programs.

Localize, transcreate, review, and optimize music and multimedia marketing content for the Canadian French market. Ensure linguistic accuracy, cultural relevance, brand consistency, and quality through copy editing, fact checking, localization QA, and market research. Serve as a market subject matter expert, advise on consumer preferences and trends, and collaborate with global language teams on terminology and content standards.

Lead linguistic quality for an account: edit and proofread localized content, perform translations and reviews, define quality expectations, run LQAs and RCAs, liaise with Apple SMEs, manage linguistic assets, coach and onboard linguists, track KPIs, and drive corrective actions and arbitration.