Machine Learning Engineer, Siri Speech
Apple
Machine Learning Engineer, Siri Speech
Job Description
Are you excited about Generative AI and Large Language Models? Are you interested in working on cutting-edge generative modeling technologies—plus the high-quality data that fuels them—to enrich billions of people? Join the Siri Speech team at Apple! We are looking for an exceptional Senior ML engineer experienced in collecting and preparing large-scale speech data, training/adapting models, and deploying them in production. You’ll advance the latest ML techniques, shape the datasets that power Siri, and dive into the details to craft experiences for millions of users worldwide. We are seeking a candidate with a consistent track record in applied ML engineering. Responsibilities in the role will include working with existing data pipelines and annotation teams to collect, clean, and analyze speech and multimodal datasets. Training large language and multimodal models on distributed back-ends, and adapting them for on-device deployment. Ensuring quality with an emphasis on data and model robustness. You will interact closely with other ML researchers, software engineers, and design teams. Your primary focus will still be enriching conversation understanding through LLM and multimodal models—now with added attention to the data that makes these models excel.
Locations
- San Francisco Bay Area, California, United States
Salary
Estimated Salary Rangemedium confidence
40,000,000 - 80,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- collecting large-scale speech dataintermediate
- preparing large-scale speech dataintermediate
- training modelsintermediate
- adapting modelsintermediate
- deploying models in productionintermediate
- advancing ML techniquesintermediate
- shaping datasetsintermediate
- working with data pipelinesintermediate
- collecting datasetsintermediate
- cleaning datasetsintermediate
- analyzing speech datasetsintermediate
- analyzing multimodal datasetsintermediate
- training large language modelsintermediate
- training multimodal modelsintermediate
- distributed back-endsintermediate
- on-device deploymentintermediate
- ensuring data qualityintermediate
- ensuring model robustnessintermediate
- interacting with ML researchersintermediate
- interacting with software engineersintermediate
- interacting with design teamsintermediate
- enriching conversation understandingintermediate
- LLMintermediate
- multimodal modelsintermediate
Required Qualifications
- 5–7 + years experience in Machine Learning applied to Speech & NLP. (experience)
- Hands-on experience training LLMs, adapting pre-trained LLMs for downstream tasks, and leveraging curated datasets or human-feedback data. (experience)
- Familiarity with large-scale data collection/processing (e.g., annotation guidance, data quality checks). (experience)
- Experience delivering ML capabilities into great products. (experience)
- Proficiency with ML toolkits such as PyTorch. (experience)
- Strong programming skills in Python and either C or C++. (experience)
Preferred Qualifications
- B.S or M.S in Computer Science, or equivalent experience (experience)
- JAX (experience)
Responsibilities
- We are seeking a candidate with a consistent track record in applied ML engineering. Responsibilities in the role will include working with existing data pipelines and annotation teams to collect, clean, and analyze speech and multimodal datasets. Training large language and multimodal models on distributed back-ends, and adapting them for on-device deployment. Ensuring quality with an emphasis on data and model robustness. You will interact closely with other ML researchers, software engineers, and design teams. Your primary focus will still be enriching conversation understanding through LLM and multimodal models—now with added attention to the data that makes these models excel.
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Machine Learning Engineer, Siri Speech
Apple
Machine Learning Engineer, Siri Speech
Job Description
Are you excited about Generative AI and Large Language Models? Are you interested in working on cutting-edge generative modeling technologies—plus the high-quality data that fuels them—to enrich billions of people? Join the Siri Speech team at Apple! We are looking for an exceptional Senior ML engineer experienced in collecting and preparing large-scale speech data, training/adapting models, and deploying them in production. You’ll advance the latest ML techniques, shape the datasets that power Siri, and dive into the details to craft experiences for millions of users worldwide. We are seeking a candidate with a consistent track record in applied ML engineering. Responsibilities in the role will include working with existing data pipelines and annotation teams to collect, clean, and analyze speech and multimodal datasets. Training large language and multimodal models on distributed back-ends, and adapting them for on-device deployment. Ensuring quality with an emphasis on data and model robustness. You will interact closely with other ML researchers, software engineers, and design teams. Your primary focus will still be enriching conversation understanding through LLM and multimodal models—now with added attention to the data that makes these models excel.
Locations
- San Francisco Bay Area, California, United States
Salary
Estimated Salary Rangemedium confidence
40,000,000 - 80,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- collecting large-scale speech dataintermediate
- preparing large-scale speech dataintermediate
- training modelsintermediate
- adapting modelsintermediate
- deploying models in productionintermediate
- advancing ML techniquesintermediate
- shaping datasetsintermediate
- working with data pipelinesintermediate
- collecting datasetsintermediate
- cleaning datasetsintermediate
- analyzing speech datasetsintermediate
- analyzing multimodal datasetsintermediate
- training large language modelsintermediate
- training multimodal modelsintermediate
- distributed back-endsintermediate
- on-device deploymentintermediate
- ensuring data qualityintermediate
- ensuring model robustnessintermediate
- interacting with ML researchersintermediate
- interacting with software engineersintermediate
- interacting with design teamsintermediate
- enriching conversation understandingintermediate
- LLMintermediate
- multimodal modelsintermediate
Required Qualifications
- 5–7 + years experience in Machine Learning applied to Speech & NLP. (experience)
- Hands-on experience training LLMs, adapting pre-trained LLMs for downstream tasks, and leveraging curated datasets or human-feedback data. (experience)
- Familiarity with large-scale data collection/processing (e.g., annotation guidance, data quality checks). (experience)
- Experience delivering ML capabilities into great products. (experience)
- Proficiency with ML toolkits such as PyTorch. (experience)
- Strong programming skills in Python and either C or C++. (experience)
Preferred Qualifications
- B.S or M.S in Computer Science, or equivalent experience (experience)
- JAX (experience)
Responsibilities
- We are seeking a candidate with a consistent track record in applied ML engineering. Responsibilities in the role will include working with existing data pipelines and annotation teams to collect, clean, and analyze speech and multimodal datasets. Training large language and multimodal models on distributed back-ends, and adapting them for on-device deployment. Ensuring quality with an emphasis on data and model robustness. You will interact closely with other ML researchers, software engineers, and design teams. Your primary focus will still be enriching conversation understanding through LLM and multimodal models—now with added attention to the data that makes these models excel.
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Engineer, Siri Speech @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs