Summary
Posted : Sep 16, 2024
Weekly Hours : 40
Role Number : 200561512
Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly.
Bring passion and dedication to your job and there’s no telling what you could accomplish.
The people here at Apple don’t just create products they create the kind of wonder that’s revolutionized entire industries.
It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.
Join Apple, and help us leave the world better than we found it.
The Product Operations team is looking for an extraordinary engineer to join our team. You will help design and implement our machine learning strategy to the substantial supply chain and help build the future of our manufacturing systems and smarter factories.
We will be collaborating and working with multi-functional teams and applying algorithms to large-scale data.
Description
Product Operations partners with a variety of different engineering and operations teams; our team leads the development of machine learning solutions.
We deliver projects from end-to-end : problem statement and conceptualization, proof-of-concept, and participation in final deployment!
You will also perform ad-hoc statistical analyses and work closely with data engineers to generate detailed business intelligence solutions.
You will be expected to conduct presentations of analyses to a wide range of audiences, including executives.
Minimum Qualifications
- 3+ years of experience in machine learning algorithms, statistics, and data mining models, with an emphasis on large language models (LLM) or large multimodal models (LMM).
- Master’s degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or a related field.
Key Qualifications
- Strong understanding of algorithms (with the ability to tweak them when necessary) and the infrastructure required for fast iterations.
- Proficient in software development, particularly in Python, with extensive experience in ML and data science libraries (e.
g., PyTorch, Scikit-learn, TensorFlow, Langchain).
- Ability to clearly and effectively communicate analysis results and to simplify complex machine learning concepts for non-technical audiences.
- Experience applying ML techniques in the manufacturing and testing domains is highly desirable.
- Hands-on experience with transformer models such as BERT, GPT, RoBERTa, and a strong understanding of their underlying principles is a plus.
- Proven experience with LLM and LMM development, including fine-tuning, is a plus.
- Proven experience in managing and mentoring teams is a plus.
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 $214,500, 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 reimbursement for certain educational expenses including tuition.
Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note : Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Company : Apple
Tagged as : Business Intelligence, Data Mining, Industry, Language Modeling, NLP, United States
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