Summary
The information below covers the role requirements, expected candidate experience, and accompanying qualifications.
Posted : Jun 12, 2024
Role Number : 200554814
The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning, and natural language processing! The features we create are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for.
Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages, and Lookup.
We also develop state-of-the-art generative AI technologies based on Large Language Models to power innovative features in both Apple’s devices and services on the cloud.
As part of this group, you will be doing large scale machine learning and deep learning to improve Open Domain Question Answering and developing fundamental building blocks needed for Artificial Intelligence.
This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries, retrieve and rank relevant documents across multiple sources, and synthesize information across documents to provide users with a direct answer that best satisfies their intent and information-seeking needs.
You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain-specific Large Language Models for various tasks and applications in Apple’s AI-powered products and conduct applied research to transfer cutting-edge research in generative AI to production-ready technologies.
Description
As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple.
We are looking for people with excellent applied machine learning experience and solid engineering skills in creating outstanding question-answering services.
This role will have the following responsibilities :
- Analyzing search ranking and relevance requirements, issues, and opportunities
- Developing, fine-tuning, and evaluating domain-specific Large Language Models for various tasks and applications in Apple’s AI-powered products
- Conducting applied research to transfer cutting-edge research in generative AI to production-ready technologies
- Understanding product requirements, translating them into modeling tasks and engineering tasks
- Building machine learned models for question answering, search relevance, ranking, and query understanding problems
- Integrating search functions into Apple products, such as Siri, Spotlight, Safari, Messages, Lookup, etc.
- Building end-to-end production systems including query understanding and ranking to power search and open domain question answering
- Utilizing Spark, Hadoop MapReduce, Hive, Impala to perform distributed data processing
Minimum Qualifications
- Experience in machine learning, deep learning / LLM, information retrieval, natural language processing
- Experience in prompt engineering, fine-tuning, evaluating, and developing data collection / annotation / management tooling for LLMs
- Proficiency in Python and at least one of the following languages : Go, Java, C++
- Excellent knowledge and good practical skills in major machine learning algorithms
- Excellent data analytical skills
- Good interpersonal skills and team player
Preferred Qualifications
- Experience with Large Scale Data-Mining and / or Machine learning is a plus
- Experience with ML and LLM model inference optimization is a plus
- MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
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 $175,800 and $312,200, 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.
Company : Apple
Apple
J-18808-Ljbffr
AIML - Machine Learning Engineer, Siri and Information Intelligence
AIML - Machine Learning Engineer, Siri and Information Intelligence. The Siri Attention and Invocation Data team is in search of a curious and innovative team player who is passionate about building and innovating our data strategy. Working closely with other teams to understand their needs and prop...
Staff Machine Learning Engineer, Ads Candidate Generation
In this role, you will spearhead the developing and executing a visionary strategy to evolve our machine learning technology stack for Candidate Generators. Be responsible for the development of state-of-the-art applied machine learning projects for ads candidate generation models. Within the Ads ca...
Machine Learning Engineer, Security AI
Documentation and Best Practices: Establish an effective process for machine learning and security operations, and maintain clear documentation of models, data pipelines, and security procedures. Continuous Learning and Adaptation: Commitment to staying abreast of the latest research and trends in d...
Senior Backend Engineer, Risk Systems - Machine Learning Platform
Proficiency or publications in modern machine learning theories and applications such as deep learning, transfer/multi-task learning, reinforcement learning, time series or graph algorithms. Build modeling infrastructures, LLM applications, labels, features and algorithms towards robustness, automat...
Machine Learning Engineer II, Annapurna ML
You will use and provide feedback to the various Neuron SDK libraries and help prototype and develop new features based on the latest research findings and customer requests. You will work directly with customer data scientists and ML engineering teams and write code to have the models be performant...
AIML - Machine Learning Engineer, Machine Learning Platform & Infrastructure
Are you someone who can write high-quality, well-tested code and collaborate cross-functionally with partner Hardware, Software, Machine Learning, and Research teams across the company? Do you have any experience building Machine Learning compilers/runtimes/kernels/optimization tools? If so, come jo...
AIML - Linguistic Annotation Project Lead, Siri Information and Intelligence
RESPONSIBILITIES INCLUDE:- Reviewing and advising the development of annotation project strategies, interfaces, and guidelines - Relaying and interpreting project guidelines and instructions for annotators - Serving as an interface for feedback and questions from annotators back to data scientists -...
Machine Learning Engineer, TikTok Content Recommendation (Ecosystem & Cold-Start)
Here, you can drive deeper into the improvement and optimization of machine learning/deep learning algorithms, including but not limited to Mathematics, CV/NLP technology, multi-task learning, multi-modal technology, meta-learning, reinforcement learning, causal inference, metric learning, graph neu...
Senior, Data Scientist - Machine Learning Engineer
Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source fr...
Machine Learning Engineer, Trust and Safety - USDS
Minimum Qualifications- BS degree with 2+ years’ industrial experience, or a MS/PhD degree with 1+ years' relevant experience- Hands on experience in one or more of the areas: machine learning, deep learning, pattern recognition, anomaly detection, data mining, computer vision, NLP or content unders...