Machine Learning Algorithm Engineer
Research and develop generative AI models and sensing algorithms for physical signals (time series, images) that power user-interaction experiences across Apple products like Mac, iPhone, iPad, and Apple Watch, taking features from prototyping through production. Core stack: Python, PyTorch, digital signal processing.
- Compensation
- Not disclosed
- Location
- Cupertino
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- BS in Computer Science, Electrical Engineering, or related STEM field with at least 3 years relevant industry or research experience
- Hands-on experience developing generative AI models or systems beyond tutorials (shipped products, publications, substantial projects)
- Experience working with real-world sensor or physical measurement data; understanding of time series and image signals and their noise structure
- Solid foundation in digital signal processing and time-series analysis (filtering, spectral analysis, feature extraction)
- Strong Python skills and proficiency with a modern deep learning framework such as PyTorch
Nice to have
- MS or PhD in machine learning, signal processing, electrical engineering, physics, or related field with publications, open-source contributions, or shipped products in generative AI
- Experience training generative or other ML models on time-series, sensor, audio, or image data, including at scale on GPU clusters
- Statistical rigor in designing experiments and evaluations, backed by reproducible research practices
- Experience using LLM-based AI assistants and agents for coding, data analysis, and experiment automation
- Proficiency in C/C++ and familiarity with embedded or resource-constrained systems
- Demonstrated persistence driving a challenging project from idea to production or real-world deployment
- Excellent communication and cross-functional collaboration across algorithms, firmware, and software
Full description
Join Apple's HID sensing and interaction algorithms team, which develops advanced sensing algorithms that enable best-in-class user experiences across Mac, iPhone, iPad, Apple Pencil, Apple Watch, and exciting new products. We are looking for a machine learning engineer with hands-on generative AI experience and a strong foundation in signal processing, who is excited to apply both to how people interact with Apple products.
Our team draws from diverse backgrounds: signal processing, machine learning, firmware, software engineering, physics, human factors, and more; all dedicated to inventing new ways users interact with Apple products. You will work at the intersection of hardware, software, and design, collaborating with specialists across Apple to ship extraordinary products to millions of users every year.
In this role, you will help explore how generative AI can advance sensing and interaction. You will research, develop, and evaluate generative models and AI systems for physical signals such as time series and images. Success here is measured by real-world impact on products and users, not by leaderboard numbers. That takes a deep understanding of the signals you model and statistical rigor in how you judge results. These are challenging, open-ended problems, and we are looking for someone with the persistence to carry an idea all the way into production.
You will also bring a solid understanding of physical signals and signal processing, and use it to develop sensing algorithms for products. You will collaborate with algorithm, firmware, and software engineers to deliver features from prototyping through production.
We value engineers who check their claims against real data, report negative results honestly, and explain technical findings clearly to people outside their field.
Minimum Qualifications
- BS in Computer Science, Electrical Engineering, or a related STEM field with a minimum of 3 years of relevant industry or research experience
- Hands-on experience developing generative AI models or systems that go beyond tutorials, such as through shipped products, publications, or substantial projects
- Experience working with real-world sensor or physical measurement data. Strong understanding of physical signals such as time series and images, and how their structure and noise shape what a model learns
- Solid foundation in digital signal processing and time-series analysis, such as filtering, spectral analysis, and feature extraction
- Strong Python programming skills and proficiency with a modern deep learning framework such as PyTorch
Preferred Qualifications
- MS or PhD in machine learning, signal processing, electrical engineering, physics, or a related field, with publications, open-source contributions, or shipped products in generative AI