Apple · Cupertino

Machine Learning Engineer

(w/m/d) · 26.3.2025

Description

To be successful, candidates will 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. Mentor other MLE’s and lead an effort to build scalable end-to-end machine learning solutions for our retail customers. RESPONSIBILITIES INCLUDE: - Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. - Contribute to the ongoing improvement of our ML infrastructure and tooling. - Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering.

Qualifications

  • 3+ 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.
  • Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc.
  • Skilled in communication, problem solving, strategic thinking.

Preferred Qualifications

  • 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.
  • Skilled in communication, problem solving, critical thinking.
  • Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus.
  • Experience with Spark, TensorFlow, Keras, and PyTorch a plus.

Benefits

Application

View listing at origin and apply!