Senior AI/ML Engineer, Tools & Infrastructure
Apple
Software Engineering, Other Engineering, Data Science
Cupertino, CA, USA
USD 181,100-318,400 / year + Equity
Posted on Jan 31, 2026
Come join a creative engineering team devoted to making our products more durable through data-driven insights. We're looking for a senior AI/ML engineer to lead the development of intelligent applications and systems that unlock the power of our hardware test data and enable hardware engineers to create their own software tools. In this role, you'll architect and build scalable AI/ML-driven software to help take our department's capabilities to the next level. You'll work with hardware and software engineering teams throughout Apple to design robust AI/ML applications, implement production-grade AI pipelines, iterate based on evolving requirements, and provide input on technical strategy. The tools and platforms you build will power processes, analytics, and workflows that directly influence the design of future products. This is a hands-on work environment where engineers are expected to be self-motivated and proficient with a wide range of AI/ML technologies, while dedicating time to leading contractor teams, driving projects forward, presenting to executive leadership, and delivering excellent solutions for Apple.
In this role you'll architect and implement AI/ML software applications and platforms for the Reliability department at Apple. You’ll provide technical leadership and bridge the gap between business needs and production software, delivering tools that automate workflows and surface novel insights for the organization.
- Architect and build robust, full-stack AI/ML applications using modern software engineering best practices, leveraging Python-based services (FastAPI), containerized deployments on Kubernetes, scalable data stores (Postgres/Timescale with vector search), and production-grade ML platforms for training, evaluation, and serving, while providing technical leadership across projects.
- Lead and mentor a team of external contractors, providing architectural guidance, code reviews, and daily direction to ensure fast, high-quality delivery.
- Drive the scope of engineering projects independently, identifying new opportunities, defining requirements, and managing the full project lifecycle from concept to deployment.
- Apply machine learning algorithms and statistical methods to solve complex business problems, focusing on rapid prototyping followed by high-quality production delivery.
- Design and implement MLOps workflows to ensure applications are scalable, monitoring their performance and reliability in production environments.
- Cultivate strong partnerships across engineering and business teams, acting as both a visionary and translator between software and non-software audiences.
- Act as the primary point of contact for stakeholders, tailoring communication to multidisciplinary audiences while delivering regular updates on project roadmaps.
- Present complex technical narratives and data-driven insights effectively to executive leadership through clear, high-impact presentations and visualizations.
- B.S. in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related field
- 4+ years experience and strong foundation in Software Engineering fundamentals, including data structures, algorithms, object-oriented design, and proficiency in building production-quality applications in Python
- 2+ years expertise in AI Engineering, using modern ML frameworks to design and deploy production-level platforms with end-to-end observability using vector-enabled data stores (e.g. Postgres/Timescale)
- Demonstrated leadership experience with the ability to lead contractors, mentor peers, and manage technical resources effectively
- Proven ability to drive projects independently: defining scope, collaborating with stakeholders, negotiating requirements, and driving projects to completion
- Solid understanding of Machine Learning algorithms, with the ability to select and implement the right model or approach for the problem at hand
- Excellent communication and presentation skills, with the ability to articulate complex technical concepts to diverse audiences and influence decision-making
- Thrives in fast-paced, evolving environments—quickly pivots priorities while maintaining data integrity and reliability
- M.S. in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related field
- Passion for quality and attention to detail; proactive in researching and assessing emerging technologies (AI/ML models, protocols, and techniques), and integrating them into production
- Experience designing and operating MLOps workflows in cloud-native environments, including CI/CD for ML systems, model versioning and promotion, scalable batch and online inference, and monitoring of data quality, model performance, and system reliability in production
- Track record of successfully growing the scope of engineering projects from initial proof-of-concept to organization-wide adoption
- 6+ years experience and strong foundation in Software Engineering fundamentals, including data structures, algorithms, object-oriented design, and proficiency in building production-quality applications
- Experience with Python (FastAPI), PyTorch, Hugging Face, and Spark to deploy production-level platforms on Kubernetes with end-to-end observability, MLflow tracking, and vector-enabled data stores (e.g. Postgres/Timescale)
- Experience with computer vision technologies and techniques, especially for segmentation, anomaly detection, and objective grading is a plus
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.