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Apple is seeking an Applied Machine Learning Engineer to join the Apple Intelligence team in Bengaluru. You will work on generative AI systems that reach billions of users globally, focusing on building production-grade solutions that are culturally and linguistically adaptable across international markets.
In this role, you'll collaborate with a dedicated team of ML and software engineers to apply and integrate generative modeling techniques into production systems. You'll own components across the full pipeline—from data preprocessing to evaluation and deployment—ensuring systems work reliably at scale. Your work will span generative technologies for key international markets, with emphasis on practical engineering rigor, clean code, and systems thinking.
You are a hands-on individual contributor with strong applied ML expertise and a passion for shipping production systems. You'll focus on debugging, performance optimization, and transitioning smoothly across evolving platforms and frameworks. The role emphasizes software development lifecycle methodologies, code quality, and the ability to troubleshoot complex systems in production.
Key areas of focus include:
- Building and integrating ML models into production workflows
- Working with generative AI systems, including LLMs and multi-agent architectures
- Implementing NLP techniques (tokenization, language modeling, decoding, classification)
- Designing and maintaining evaluation environments for repeatable testing
- Collaborating on architectural discussions and code reviews
- Leveraging modern AI coding tools (Claude, Cursor, Codex) in development
Requirements:
- 5+ years of hands-on ML experience building and integrating models into production workflows
- Proficiency in Python plus one or more of C/C++/Objective-C/Swift
- Strong software engineering foundation (OS fundamentals, object-oriented programming)
- Proven track record as a hands-on individual contributor shipping clean, well-tested, maintainable code
- Practical experience with generative AI coding tools (Claude, Cursor, Codex)
- Strong debugging, systems-thinking, and problem-solving skills demonstrated through code reviews and production troubleshooting
- Applied experience with NLP (tokenization, language modeling, decoding, classification)
- Experience with modern agentic and multi-agent systems
- Familiarity with RAG (Retrieval-Augmented Generation) architectures
Preferred Qualifications:
- Experience staging, provisioning, or controlling test/evaluation environments for repeatable, deterministic conditions
- Experience evaluating ML, LLM, or agent-based systems with knowledge of metrics and scoring methodology
- Production experience building, maintaining, or operating AI agents at scale
- Exposure to deep learning libraries (PyTorch, TensorFlow)
- Background in developer tools, internal platforms, or productivity engineering
- Strong communication skills (written and verbal) with ability to share knowledge and elevate team quality
