Summary
Posted: Aug 31, 2024
Role Number:200565509
At Apple, we're revolutionizing the way people interact with technology. The Siri Perception team is dedicated to creating innovative voice-based experiences that make our products more intuitive and personal. We are seeking a talented Machine Learning Engineer to join our team and help us develop the next generation of Siri on Apple Intelligence. Our Back to Back feature is an advancement in voice based technology that enables Siri to understand when the user is talking to Siri and when they are not without even needing to say "Siri" or "Hey Siri". As a Machine Learning Engineer, you will play a crucial role in designing, developing, and implementing machine learning algorithms to power this feature. You will work closely with a team of talented engineers, researchers, and data scientists to explore new approaches, conduct experiments, and analyze data to improve our user journeys!
Want more jobs like this?
Get Data and Analytics jobs in San Francisco, CA delivered to your inbox every week.
Description
As a Machine Learning Engineer, you will be responsible for developing and applying machine learning techniques to improve Siri's ability to understand and respond to user queries in real-time. You will work on a variety of tasks including: • Designing, developing, and implementing machine learning models to power Siri invocation features. This will involve data analysis, experimentation, and modeling to create user journeys that are seamless and intuitive. • Conducting experiments to evaluate the performance of machine learning models and identify areas for improvement • Conducting error estimation and monitoring distribution shifts to ensure model performance and robustness. • Collaborating with cross-functional teams to productionize next generation of machine learning models for Siri invocation • Staying up-to-date on the latest advances in machine learning and applying them to Siri's development
- Master's degree in Computer Science, Machine Learning, or a related field
- Strong programming skills in Python
- Experience with machine learning frameworks such as TensorFlow or PyTorch
- Excellent problem-solving, quantitative and analytical skills
- Ability to work independently and as part of a team
Preferred Qualifications
- Master's degree or PhD in Computer Science, Machine Learning, or a related field
- Experience with speech recognition and natural language processing
- Knowledge of deep learning architectures, including LLMs
- Experience working on large-scale machine learning projects
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 $143,100 and $264,200, 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.
More
- 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.