AIML - Machine Learning Engineer, NLP - Siri and Information Intelligence
1 week ago
Summary: 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? Do you want to expand the experience of Siri and other AIML products to new products that will help millions get things done, across the globe? 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
Description:
- Develop 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 Qualifications:
- Strong 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.
Key Qualifications Preferred Qualifications:
- Prior 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.
Education & Experience Additional Requirements:
Pay & Benefits:
- 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 $135,400 and $250,600, and your base pay will depend on your skills, qualifications, experience, and location.
- Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
- Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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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