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Machine Learning Speech Jobs (NOW HIRING)

The Machine Learning Platform Technology team is building groundbreaking technology for search ... You will have a chance to work on optimizing billions of parameter language and vision and speech ...

Machine Learning Research Intern, Audio As a Research Intern at Bland, you will own a focused research project across our voice stack: speech-to-text, large language models, neural audio codecs, or ...

$150K - $225K/yr

Cupertino, California, United States Machine Learning and AI Play a part in building the next revolution in speech and machine learning technology. We're looking for passionate researchers to work on ...

The Machine Learning Platform Technology team is building groundbreaking technology for search ... You will have a chance to work on optimizing billions of parameter language and vision and speech ...

... machine-learning team in the speech technology space 7+ years in a hands-on machine learning role with demonstrable product impact Experience taking responsibility and ownership of features and the ...

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.) * Experience with ...

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.) * Experience with ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for ... understanding, speech-audio modeling) and dataset optimization for model training. • Solid ...

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Machine Learning Speech information

What is a machine learning speech engineer?

A Machine Learning Speech Engineer is a professional who develops algorithms and models that enable computers to understand, process, and generate human speech. They work on tasks such as speech recognition, speech synthesis, speaker identification, and natural language understanding, often utilizing deep learning and other machine learning techniques. Their work is crucial for applications like virtual assistants, transcription services, and voice-controlled devices. These engineers typically have a background in computer science, linguistics, signal processing, and machine learning.

What are the key skills and qualifications needed to thrive as a machine learning speech engineer, and why are they important?

To thrive as a Machine Learning Speech Engineer, you need a solid background in computer science, signal processing, and machine learning, often supported by an advanced degree in a related field. Familiarity with tools like TensorFlow, PyTorch, Kaldi, and experience with speech recognition or natural language processing systems are typically required. Strong problem-solving skills, collaboration, and effective communication help in translating complex research into practical speech solutions. These competencies are vital for developing accurate and efficient speech technologies that meet user and business needs.

What are the typical collaboration opportunities for a machine learning speech engineer within a company?

Machine Learning Speech engineers frequently collaborate with cross-functional teams, including data scientists, software developers, product managers, and linguists. They work together to design, train, and deploy speech recognition or synthesis models, ensuring alignment with the company’s product goals and user needs. Collaboration is essential for integrating speech technologies into larger systems, troubleshooting issues, and refining models based on real-world feedback. Regular communication and teamwork help drive innovation and ensure the speech solutions are robust and user-friendly.

What is the difference between Machine Learning Speech vs Speech Recognition Engineer?

AspectMachine Learning SpeechSpeech Recognition Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Electrical Engineering, Computer Science; experience with speech processing tools
Work EnvironmentResearch labs, tech companies, AI startupsTech companies, voice tech firms, R&D departments
Industry UsageDevelops models for speech understanding, synthesis, and processingBuilds and optimizes speech recognition systems and algorithms

Machine Learning Speech focuses on developing models for understanding and generating speech, often involving deep learning techniques. Speech Recognition Engineers specialize in creating systems that convert spoken language into text. While both roles require knowledge of speech technologies, Machine Learning Speech emphasizes model development, whereas Speech Recognition Engineers focus on system implementation and optimization.

Infographic showing various Machine Learning Speech job openings in the United States as of September 2026, with employment types broken down into 10% Internship, 70% Full Time, 10% Part Time, and 10% Contract. Highlights an 90% In-person, and 10% Remote job distribution.

AIML - Machine Learning Researcher, Speech

Cupertino, CA • On-site

Apple
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Re-posted 15 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 684 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Play a part in building the next revolution in speech and machine learning technology. We're looking for passionate researchers to work on ambitious, curiosity-driven, long-term speech research projects. In this role, you'll have the opportunity to work on innovative foundational research in speech technology and machine learning. As a member of the team, you will be inspired by a diversity of challenging problems, collaborate with world-class machine learning engineers and researchers to impact the future of Apple products, and publish some of your results in high-quality scientific venues.
Description
In this position, you will be responsible for pushing the boundaries of machine learning research, with a focus on running state-of-the-art speech models efficiently on-device. You will collaborate with researchers to push the state-of-the-art in the speech domain, specifically focusing on ASR and speech language models. You will publish your results in top conferences, making sure that your research results are reproducible and of high quality. You will prepare technical reports for publication and conference talks, and have the opportunity to collaborate with broader teams across Apple.
Minimum Qualifications
Demonstrated expertise in machine learning research
Publication record in relevant machine learning conferences (e.g., NeurIPS, ICML, ICLR, etc.) and/or relevant speech conference/Journals (e.g., Interspeech, ICASSP, ASRU, etc.)
Hands-on experience working with deep learning toolkits such as PyTorch
Strong mathematical skills in linear algebra and statistics
PhD, or equivalent practical experience, in Computer Science, or related technical field.
Preferred Qualifications
Ability to formulate a research problem and design, experiment, implement, and communicate solutions.
Ability to work in a diverse, collaborative environment
High-quality open-source contributions to related projects
Strong presentation skills for internal and external communications.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976