As a Software Engineer on our team you will play a pivotal role in shaping and delivering high-impact AI/ML solutions that redefine how Apple designs manufactures and tests hardware products. The software you build will power data-driven decisions uncover new insights and enable breakthrough capabilities across Hardware Engineering and operate in a fast-paced collaborative environment working closely with cross-functional teams to quickly iterate validate and deploy practical AI/ML solutions at Responsibilities:-Design implement and maintain AI/ML software solutions with clean scalable and testable code-Collaborate with senior engineers and cross-functional partners to understand requirements and translate them into concrete technical tasks-Develop and refine ML workflows including training evaluation and inference pipelines for both traditional models and LLM-based solutions-Contribute to agentic system development and RAG-based architectures that enable intelligent automation and reasoning-Stay up to date with the evolving AI/ML landscape and help improve our tools infrastructure and practices based on new developments-Participate in code reviews design discussions and documentation to ensure high engineering quality and team knowledge sharing-Support testing deployment and monitoring of models and services in production environments
3 years of professional software engineering experience with a focus on AI/ML development
Proficiency in Python or another object-oriented programming language
Hands-on experience with training and deploying ML models or using LLMs in applications
Strong problem-solving skills and an ability to learn quickly in a fast-paced environment
Bachelors degree in Computer Science Engineering or a related field or equivalent industry experience
Strong communication skills and a collaborative mindset
Exposure to agentic workflows RAG pipelines or LLM APIs (e.g. OpenAI HuggingFace LangChain)
Experience with ML infrastructure tools (e.g. PyTorch TensorFlow Ray Airflow)
Familiarity with containerization (e.g. Docker) CI/CD and cloud-based development
Passion for continuous learning knowledge-sharing and improving how teams build AI/ML systems
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