Machine Learning Engineer, Siri Speech

Cupertino, California, United States Software and Services

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better.

It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Come join us and do your best work. Here at Apple, you’ll do more than join something — you’ll add something. Join the Siri Speech team and play a part in the next revolution in human‑computer interaction.

You’ll help create groundbreaking technology for large‑scale systems, spoken language, big data, and artificial intelligence, building production‑quality models that power natural voice experiences used by millions. In this role, you will design and develop machine learning models, fine tune deep learning systems for speaker recognition and multimodal understanding, and collaborate across software engineering, data science, and product to integrate solutions into production.

At the Siri Speech team, you will drive research and development for natural voice interaction, investigating new approaches and fine tuning deep learning models. You will design, develop, and implement machine learning models across speech, NLP, and multimodal applications, integrate ML solutions into existing workflows and large‑scale systems, and work with large quantities of data to create production‑quality models  will write clean, efficient, well‑documented code, participate in code reviews, and mentor junior team members.

Collaboration with cross‑functional partners to define requirements and deliver high‑quality solutions is essential. You will contribute to research initiatives and stay current with advancements in ML, HCI, LLMs, speech recognition, and signal processing. You should be passionate about creating and shipping phenomenal products and thrive in a fast‑paced environment with rapidly changing priorities.

• Design, develop, and implement machine learning models for speech, NLP, and multimodal applications.
• Investigate and fine tune deep learning architectures for natural voice interaction and speaker recognition.
• Integrate ML solutions into production systems and existing workflows at scale.
• Collaborate with data scientists, software engineers, and product managers to define requirements and deliverables.
• Write clean, efficient, well‑documented code and participate in code reviews.
• Analyze large datasets and apply state‑of‑the‑art methods to build production‑quality models.
• Mentor junior team members and contribute to engineering best practices.
• Stay current with advances in ML, HCI, LLMs, speech recognition, and signal processing and contribute to research.

• Strong proficiency in Python; good coding skills in bash scripting, and any OOP/functional language such as Java, C, C++, Go, Rust etc.
• Experience with machine learning algorithms and techniques, including deep learning.
• Hands‑on experience with Tensor Flow and/or PyTorch; familiarity with scikit‑learn.
• Experience with version control systems such as Git.
• Good knowledge in machine learning technologies related to speech and audio processing; experience with image processing is a plus.
• Strong problem‑solving skills and ability to work independently as well as in a team environment.
• Excellent written and verbal communication skills.

• M.S in Computer Science or related field, or Bachelor’s degree with equivalent experience.

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 $147,400 and $220,900, and your base pay will depend on your skills, qualifications, experience, and location.

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