Research Engineer / Scientist
Apple
Listing collected from Apple's career site. NextChapter is independent of Apple.
Cupertino, CA · Posted October 27, 2026
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Engineering jobs in the rankings
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing does not state pay. Across 69 open research engineer listings that state pay, the middle half runs $237,500 to $425,000 and the median is $285,000.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
AI use among mechanical engineers is little observed so far. Measured exposure for mechanical engineers: 8% (little observed).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Apple has filed 4 layoff notices in the last twelve months, covering 225 workers, most recently August 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings
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About the job
Apple is revolutionizing artificial intelligence by developing sophisticated foundation models that power intelligent features across our product ecosystem. We're seeking skilled Machine Learning Engineers to transform cutting-edge research into scalable, production-ready AI solutions. We are looking for engineers who are passionate about building systems that push the frontier of deep learning in terms of scaling, efficiency, and flexibility and delight millions of users in Apple products.
We build the foundation models behind intelligent experiences across Apple products, from high-performance server models to highly efficient on-device models, all designed for Apple silicon and for private, personal use. How good these models get depends on the data they learn from and on how well we measure them.
We are looking for a technical leader to drive training data and model evaluation across the foundation model training lifecycle, from pre-training and mid-training through post-training. You will influence our strategy for data development: data at scale, at high quality, compliant with privacy and policy requirements, and targeted through curation and synthesis based on product feedback. You will also drive evaluation that steers model training and predicts real user experience.