Applied AI Engineer – Global Siri

Apple

7h

About The Position

The Global Siri team builds the next generation of Siri AI agents for users around the world. The Applied AI Engineer works across the machine-learning lifecycle—including data, modeling, evaluation, and deployment—to develop and ship data, models, and systems that bring Siri AI features to new languages and markets and improve quality in existing markets. The role collaborates with Siri modeling, evaluation, data science, and deployment teams, as well as Apple’s Modeling, ML Platform, and Safety teams.

The work includes building scalable processes, agents, and pipelines to curate, filter, deduplicate, augment, and version multilingual data, including fine-tuning sets, tool-use trajectories, evaluation sets, and synthetic data. The engineer applies generative AI, NLP, and ML methods to improve Siri’s understanding and responses across languages, identifies and addresses locale-specific quality gaps, and builds large-scale multilingual evaluation systems for agentic models. The role also uses agents and AI-assisted coding to automate internationalization work, prioritizes improvements using metrics and analysis, and communicates findings and recommendations to executives and partner teams to inform priorities and launch decisions.

Requirements

• B.S. or M.S. in Computer Science or a related field, or equivalent experience.
• Strong software engineering fundamentals and proficiency in Python.
• Hands-on experience across the machine-learning lifecycle, including data, training, evaluation, and deployment.
• Strong understanding of LLMs, NLP, and machine learning and their applications.
• Hands-on experience with ASR, acoustic triggering, or TTS in international locales, including accents, code-switching, low-resource languages, and locale-specific metrics.
• Extensive hands-on experience with agentic AI-assisted coding and context engineering.
• An analytical, data-driven mindset and experience.
• Experience building and debugging production services or data products end to end.
• Excellent communication skills and ability to work across teams in an English-speaking environment.
• Strong written and verbal communication skills.
• Agentic coding and generative AI as a daily way of working, including building agents or workflows to automate real engineering and data tasks.

Nice To Haves

• Experience building synthetic data generation pipelines and using them to launch features or improve product metrics, especially where real data is scarce.
• Experience with large-scale data or ML infrastructure, such as Spark or Kubernetes, and LLM evaluation methods such as LLM-as-judge.
• A track record of shipping user-facing ML features in multiple languages or markets.

Responsibilities

• Build scalable processes, agents, and pipelines to curate, filter, deduplicate, augment, and version multilingual Siri AI data, including fine-tuning sets, tool-use trajectories, evaluation sets, and synthetic data.
• Apply generative AI, NLP, and machine-learning methods to improve Siri’s understanding and responses across languages and identify and fix locale-specific quality gaps.
• Build systems to run large multilingual evaluation suites for agentic models consistently and quickly across markets.
• Use agents and AI-assisted coding to automate internationalization tasks such as data generation, annotation, error analysis, and localization quality assurance.
• Use metrics and analysis to prioritize markets, languages, and failure types.
• Communicate findings, tradeoffs, and recommendations to executives and partner teams to shape priorities and launch decisions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level