Apple Inc.
AIML - Machine Learning Engineer, NLP - Siri and Information Intelligence
Apple Inc., Seattle, Washington, us, 98127
AIML - Machine Learning Engineer, NLP - Siri and Information Intelligence
As part of Apple Intelligence, the Siri team is at the forefront of the next revolution in machine learning and Generative AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new client devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. Does the opportunity to play a part in building groundbreaking technology for large-scale systems, natural language and artificial intelligence excite you? Join the ML Systems Evaluation Engineering (MLSEE) team at Apple and contribute to a highly accomplished team that evaluates AIML products that will delight and inspire millions of people!We are seeking a highly skilled Machine Learning Engineer with expertise in developing and deploying applications powered by large language models (LLMs). The ideal candidate will have robust big data management and analytical skills, and be proficient in designing applications and services that encompass all phases of the model development lifecycle, including data curation, fine-tuning, evaluation, deployment, and serving.DescriptionDevelop or fine-tune machine learning models, including LLMs, for various applications, ensuring high accuracy and performance.Design and implement ETL pipelines and data processing workflows using technologies such as AWS, Spark, and Airflow.Build and deploy APIs to provide seamless access to machine learning models.Engage in prompt engineering to create high-quality synthetic datasets for model training and evaluation.Maintain and manage deployments using Kubernetes and related technologies.Collaborate with cross-functional teams to understand project requirements and deliver scalable solutions.Minimum QualificationsStrong programming skills in Objective Oriented Programming and system design using Python (or other languages).Experience with cloud services like AWS (S3, ECS, Lambda) and container orchestration using Kubernetes.Knowledge of big data technologies like Spark, Airflow, and Trino, and familiarity with databases like Snowflake, MySQL, PostgreSQL.Experience with data visualization and reporting tools such as Tableau.Preferred QualificationsPrior experience in machine learning or related scientific research.Demonstrated ability to manage large datasets, generate synthetic data, fine-tune models, and conduct comprehensive statistical evaluations.Excellent problem-solving, communication, and teamwork skills.Proven experience in designing and building scalable applications and services.Advanced degree in Computer Science, Machine Learning, or a related field is preferred.Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
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As part of Apple Intelligence, the Siri team is at the forefront of the next revolution in machine learning and Generative AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new client devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. Does the opportunity to play a part in building groundbreaking technology for large-scale systems, natural language and artificial intelligence excite you? Join the ML Systems Evaluation Engineering (MLSEE) team at Apple and contribute to a highly accomplished team that evaluates AIML products that will delight and inspire millions of people!We are seeking a highly skilled Machine Learning Engineer with expertise in developing and deploying applications powered by large language models (LLMs). The ideal candidate will have robust big data management and analytical skills, and be proficient in designing applications and services that encompass all phases of the model development lifecycle, including data curation, fine-tuning, evaluation, deployment, and serving.DescriptionDevelop or fine-tune machine learning models, including LLMs, for various applications, ensuring high accuracy and performance.Design and implement ETL pipelines and data processing workflows using technologies such as AWS, Spark, and Airflow.Build and deploy APIs to provide seamless access to machine learning models.Engage in prompt engineering to create high-quality synthetic datasets for model training and evaluation.Maintain and manage deployments using Kubernetes and related technologies.Collaborate with cross-functional teams to understand project requirements and deliver scalable solutions.Minimum QualificationsStrong programming skills in Objective Oriented Programming and system design using Python (or other languages).Experience with cloud services like AWS (S3, ECS, Lambda) and container orchestration using Kubernetes.Knowledge of big data technologies like Spark, Airflow, and Trino, and familiarity with databases like Snowflake, MySQL, PostgreSQL.Experience with data visualization and reporting tools such as Tableau.Preferred QualificationsPrior experience in machine learning or related scientific research.Demonstrated ability to manage large datasets, generate synthetic data, fine-tune models, and conduct comprehensive statistical evaluations.Excellent problem-solving, communication, and teamwork skills.Proven experience in designing and building scalable applications and services.Advanced degree in Computer Science, Machine Learning, or a related field is preferred.Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
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