Machine Learning Engineer - Apple Store Online
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
To be successful you need a strong machine learning background proven software development skills a love of learning and to collaborate with cross-functional teams including researchers engineers data scientists/analysts and product managers to develop and implement machine learning algorithms. Youll mentor other MLEs and lead an effort to build scalable end-to-end machine learning solutions for our retail customers
- 7 years of related experience building high throughput scalable applications or building machine learning models
- Proficiency in one or more object-oriented programming languages such as Python Java C and experience building distributed systems
- Skilled in communication problem solving strategic thinking
- Bachelors in a quantitative field such as Computer Science Applied Mathematics or Statistics or equivalent professional experience
- Ph.D. or Masters in a quantitative field such as Computer Science Applied Mathematics or Statistics or equivalent professional experience
- Experience in Recommender Systems Personalization Search Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture
- Experience with building data processing pipelines large scale machine learning systems and big data technologies (eg: Spark SQL Snowflake/Hadoop etc)
- Proficiency in one or more object-oriented programming languages such as Python Java C and experience building highly scalable distributed systems
Key Skills
- Business
- Marketing
- User Interface
- Web Content
- A/B
- Communication
- CRM
- Paid Search
- HTML
- Project Management
- Content Marketing
- Email Campaigns
- ROI
- Digital strategy
- Analytics
About Company
We at AppleOne have one true belief. We believe in people. Since 1964, we have connected the best people, their talents, skills, career goals, and aspirations with the best companies. We are Career Gurus. We are People-People. Let us introduce you!
