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Manager Linguistic Annotation Jobs in California

You will work cross-functionally with Engineering and Project Managers, Product, and Governance ... Experience working with large datasets, annotation tools, and model evaluation pipelines ...

Work cross-functionally with engineers, data scientists, product managers, and content strategists ... Experience designing and implementing evaluation frameworks, annotation guidelines, or quality ...

Work cross-functionally with engineers, data scientists, product managers, and content strategists ... Experience designing and implementing evaluation frameworks, annotation guidelines, or quality ...

Showing results 21-40

Manager Linguistic Annotation information

What are the key skills and qualifications needed to thrive as a manager linguistic annotation?

To thrive as a Manager Linguistic Annotation, you need expertise in linguistics or computational linguistics, experience with annotation projects, and often an advanced degree in a related field. Familiarity with annotation tools, data management systems, and project management software is typically required. Strong leadership, communication, and organizational skills help manage teams, meet deadlines, and ensure high-quality output. These abilities are crucial for overseeing complex annotation workflows and delivering accurate linguistic data for AI and NLP applications.

What is a manager linguistic annotation?

Manager Linguistic Annotation jobs involve overseeing teams that label and annotate linguistic data, such as text, audio, or speech, to train and improve artificial intelligence and natural language processing systems. These managers are responsible for project planning, quality assurance, and ensuring that annotation guidelines are followed. They often collaborate with linguists, data scientists, and engineers to deliver high-quality annotated datasets on time. Strong communication skills, attention to detail, and experience in linguistics or language technology are typically required for this role.

How does a manager linguistic annotation typically collaborate with cross-functional teams to ensure project success?

A Manager of Linguistic Annotation frequently works alongside data scientists, computational linguists, software engineers, and product managers to align annotation guidelines with project goals. This role involves coordinating annotation tasks, clarifying linguistic requirements, and ensuring data quality through regular feedback sessions. Effective communication and the ability to translate linguistic concepts for non-specialist teammates are crucial. By fostering collaboration, the manager ensures that annotated datasets are accurate, consistent, and useful for downstream applications such as machine learning models.
What are the most commonly searched types of Linguistic Annotation jobs in California? The most popular types of Linguistic Annotation jobs in California are:
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Engineering Project Manager - AI Features Internationalization, L&RE

Apple

Cupertino, CA

$144K - $263K/yr

Full-time

Medical, Dental, Retirement

Re-posted 9 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Apple's Software Engineering Operations (SWE Ops) organization is seeking a highly technical Engineering Project Manager (EPM) to drive the internationalization and global launch of AI-driven products, including Apple Intelligence and new hardware with integrated ML capabilities.
Description
In this role, you will lead the technical integration of generative AI and machine learning features across 25+ languages and 40+ countries. You will sit at the critical intersection of Core ML Modeling, Data Science, Hardware Engineering, and Global Product Readiness. You are not just managing localization work-you are managing the technical dependencies, data pipelines, and model evaluation required to ensure Apple's AI features perform with high accuracy, safety, and cultural relevance worldwide. You will be responsible for the end-to-end execution of international features, from initial data collection and model evaluation to final software and hardware integration.","responsibilities":"AI Feature Orchestration: Facilitate deep technical coordination between Core ML, Software Engineering, Hardware Engineering, and Product Design to integrate AI features into international locales across software and hardware products.
End-to-End Schedule Management: Produce and manage the master schedule for i18n deliverables, ensuring all cross-functional dependencies-from model training and fine-tuning to UI implementation and hardware readiness-are aligned for global launch.
AI Data Operations: Direct the lifecycle of international data generation. Lead timelines for data collection, seek budget approvals for global datasets, coordinate with data collection teams and vendors, and iterate on "data playbooks" to improve model evaluation across diverse languages and regions.
Model Evaluation and Quality: Drive international model evaluation strategy across audio, vision, language, and fusion models. Ensure eval coverage exists for target markets and identify performance gaps that could impact the customer experience internationally.
Hardware-Software AI Integration: Drive international readiness for AI features that span hardware, on-device ML, and companion software-coordinating across hardware engineering, NPS, and regional QA teams for new product introductions (NPI).
Technical Risk and Mitigation: Proactively identify and mitigate risks unique to global AI, such as linguistic bias, cultural representation gaps in vision models, regional model performance degradation, and data collection constraints in international markets.
Stakeholder Leadership: Navigate complex internal organizations to surface risks, drive decisions on feature-by-country gating, and provide clear status to executive stakeholders across engineering, product marketing, and program leadership.
Preferred Qualifications
AI/ML Domain Depth: Hands-on experience driving AI/ML feature work, including familiarity with Large Language Models (LLMs), vision models, Natural Language Processing (NLP), or model evaluation frameworks.
New Product Introduction (NPI): Experience with international launch of hardware products containing ML/AI capabilities, including hardware access restrictions, data collection logistics, and field testing approvals.
Data Pipeline Management: Experience managing large-scale data generation, annotation, and evaluation workflows specifically for non-English locales and diverse cultural contexts.
i18n Engineering Standards: Technical knowledge of internationalization standards (e.g., Unicode, CLDR) and the architectural challenges of scaling models globally.
Fairness and Inclusion: Experience with demographic representation in ML training data and evaluation, including cultural and religious diversity considerations.
Budget and Resource Strategy: Experience managing significant budgets for international data acquisition and coordinating with global data vendors.
Analytical Proficiency: Ability to use data tools (e.g., SQL, Python, or internal dashboards) to track model performance, project health, and other analytics.
Minimum Qualifications
5+ years of experience as an Engineering Program/Project Manager (EPM), Technical Program Manager (TPM), or similar technical leadership role within a software or hardware engineering organization.
Technical Lifecycle Mastery: Proven track record of managing the end-to-end development lifecycle for complex, multi-team features spanning software and hardware.
Cross-Functional Leadership: Demonstrated ability to manage complex dependencies across backend engineering (Modeling/Core ML), front-end implementation, hardware, and QA teams across multiple organizations.
International Product Expertise: Direct experience shipping products globally, with a deep understanding of internationalization (i18n) and the architectural and data challenges of scaling AI features for global markets.
Navigating Ambiguity: Ability to drive projects independently, make sound technical decisions with incomplete information, and influence teams without direct authority.
Communication: Ability to translate highly technical AI/ML concepts into clear, "lightweight" executive-level status updates and risk assessments.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $144,600 and $263,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

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Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976