AIML - Senior Software Engineer, ML Systems and Evaluation Engineering
Job Description
Summary
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something.
As part of Apple Intelligence, Siri team is at the forefront of the next revolution in machine learning and Generative AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new client devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. Does the opportunity to play a part in building groundbreaking technology for large-scale systems, natural language and artificial intelligence excite you? Do you want to expand the experience of Siri and other AIML products to new products that will help millions get things done, across the globe? Join the ML Systems Evaluation Engineering (MLSEE) team at Apple and contribute to a highly accomplished team that evaluates AIML products, that will delight and inspire millions of people!
As part of Apple Intelligence, Siri team is at the forefront of the next revolution in machine learning and Generative AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new client devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. Does the opportunity to play a part in building groundbreaking technology for large-scale systems, natural language and artificial intelligence excite you? Do you want to expand the experience of Siri and other AIML products to new products that will help millions get things done, across the globe? Join the ML Systems Evaluation Engineering (MLSEE) team at Apple and contribute to a highly accomplished team that evaluates AIML products, that will delight and inspire millions of people!
Description
You will own requirements, including \'proof of concept\' development, and co-own the development roadmap for ML system evaluation platform. The ideal candidate will have a proven track record in defining success by completing the full product cycle, from design and implementation to gathering feedback and iterating on systems, frameworks, and tools for the AIML teams. This stellar engineer will oversee system integration and contribute to how their software is used in evaluation plans and continuous integration of ML models. The quintessential candidate will help build, measure, and leverage their software to provide insights into the impact of platform changes. This individual thrives in fast-paced settings, leveraging a strategic mindset for problem-solving and driving innovative enhancements to Apple product user experiences.
Minimum Qualifications
- 5+ years of professional experience in software development, with a strong emphasis on designing, implementing, and optimizing large-scale data and compute-intensive pipelines, tools, and machine learning (ML) systems.
- Strong software engineering skills, including system design, development, testing, debugging, release and maintenance.
- Proven expertise in Python (required) and at least one other object-oriented programming language (e.g., Swift, C#, Go, Java).
- Experience with the full lifecycle of ModelOps pipelines, including data preprocessing, model training, evaluation, deployment, and monitoring.
- Excellent communication and documentation skills.
Preferred Qualifications
- Knowledge of statistics based evaluation approaches, ML training pipelines and accuracy improvements of ML systems (Preferred).
- Ability to develop long-term strategic visions and execute scalable solutions in fast-paced, agile work environments.
- Strong organizational skills and experience working with multiple stakeholders.
- Big Data pipeline experience is a huge plus
