Senior Machine Learning Engineer (MAPS) at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Generative AI, NLP, Knowledge Graphs, Computer Vision, Reinforcement Learning, Policy Optimization, Python, Scala, Java, C++, Spark, PyTorch, TensorFlow, Scikit-learn

Industry

Computers and Electronics Manufacturing

Description

Are you a self-starter looking for an exciting career opportunity? Do you like to ship Data Science and Machine Learning solutions that impact millions of users around the world? A job at Apple is unlike any other you’ve had. You’ll be challenged, inspired, and you will be proud of your work. Maps are a significant part of our everyday lives. Whether you are looking for the nearest gas station, finding a transit route that gets you to the big game before kickoff, or selecting a peculiar restaurant for dinner with friends, you are relying on information and features from the Maps Engineering Team. At Apple, our team provides the foundation for building extraordinary customer experiences, with features that have become an indispensable part of so many lives around the world. We are looking for a Machine Learning Scientist/Engineer who takes full ownership of projects end to end, from initial data mining and research to prototyping, development, and final integration of AI/ML data solutions into production code that reaches millions of users. DESCRIPTION We are looking for a Machine Learning Scientist/Engineer to join our team and help shape the future of Apple Maps. In this role, you’ll work alongside world-class engineers and scientists to develop innovative AI/ML solutions that enhance user experiences. Your primary responsibility will be transforming high-level business objectives into measurable, technical requirements, including designing, implementing, and deploying cutting-edge models that solve real-world challenges. You’ll collaborate closely with cross-functional teams, including engineering and design, to architect scalable systems while continuously refining solutions through data-driven iteration. The ideal candidate takes initiative, demonstrates ownership from concept to production, is not afraid to dive deep into data, and is hands-on in building robust, real-world solutions. They thrive in a fast-paced environment and bring resilience and curiosity to continually improve in pursuit of excellence. MINIMUM QUALIFICATIONS 5+ years of experience in building large-scale machine learning systems 5+ years of experience in one or more of the following ML areas: generative AI models (e.g. Transformers, LLMs, VLMs, MLLMs), NLP, Knowledge Graphs, or Computer Vision Hands-on experience with reinforcement learning (RL), including policy optimization methods (e.g., policy gradients, actor-critic, PPO-style approaches) and deploying RL systems for large-scale models in real-world production environments Experience working with large-scale and real-world datasets Metrics-driven and passionate about delivering models that produce high-quality, user-facing results Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn; programming skills in Python, Scala, Java, or C++ Strong knowledge of Spark or other related big data technologies PREFERRED QUALIFICATIONS Masters or PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields. Hands on experience with reinforcement learning or multi-modal foundation models and understanding of state of the art approaches in the field Experience shipping a complex AI system, including research and leveraging generative AI models Excellent independent problem-solving skills Excellent written and oral communication skills

Responsibilities

The role involves transforming high-level business objectives into measurable technical requirements and developing AI/ML solutions that enhance user experiences. The candidate will collaborate with cross-functional teams to architect scalable systems and refine solutions through data-driven iteration.