Apple Media Products - Research/Machine Learning Engineer, Analytics
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
- 5+ years of programming experience, preferably in Java, Scala or Python
- Proficiency in Spark, Hadoop or other big data processing technologies
- Knowledge of Machine Learning algorithms and models
- Experience with productionalizing Machine Learning projects
- Strong engineering design skills, with a deep knowledge of data structures and algorithms
- Excellent interpersonal skills
- Strong sense of initiative and ability to drive projects to completion
- Knowledge of building Machine Learning system as an online service is a plus
The Machine Learning Engineering team is responsible for building common solutions that can be validated across AMP Engineering organization, especially in the analytics space. We invest heavily in building common libraries, frameworks or systems that can make machine learning projects in AMP easier for data scientists and engineers, more manageable and scale to our ever growing business. To achieve that mission, we are looking for a machine learning engineer who knows both worlds, ML and engineering; especially has proven engineering skills — you will be encouraged to write code that is robust, reusable, testable and maintainable, paying special attention to data quality and performance details. Communication also matters — you are encouraged to clarify the requirements, present your design proposals to the team, and work with partners effectively on the project. Partnership is also important to you — you readily contribute to design discussions, and are able to both give and receive constructive feedback and review. Your curiosity drives you to explore new technologies and apply creative solutions to problems at hand.
Education & Experience
BS degree in Computer Science, related field or equivalent experience. MS or PHD preferred. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.