We're building the next generation of AI evaluation systems — and we're looking for a
hands-on engineer who can bridge ML, software, and product to make AI systems more
measurable, testable, and trustworthy.
We’re part of the AI/ML Evaluation organization, seeking a Senior or Staff-level Applied
ML Engineer with strong software engineering skills and a solid understanding of
machine learning. In this hands-on role, you’ll help design and build intelligent systems
that simulate complex interactions (including agentic workflows powered by LLMs),
develop tools for extracting structured insights, and create robust evaluation datasets.
You’ll also contribute to building scalable platforms for simulation and behavior analysis.
This role sits at the intersection of ML, engineering, and product — ideal for someone
passionate about bringing clarity and rigor to real-world AI performance.
Description
We’re looking for a pragmatic engineer who thrives at the intersection of machine
learning and software development — capable of building robust, scalable systems that
support evaluation and development of advanced AI capabilities, including large
language models and agentic behaviors.
A successful candidate is comfortable navigating ML, systems, and product domains.
You bring strong software engineering fundamentals, experience building and
maintaining end-to-end pipelines, and a practical understanding of how to evaluate AI
systems in real-world contexts. You’re curious about how LLMs behave in interactive or
agentic settings, thoughtful about evaluation design, and eager to build tools that
improve visibility and trust in AI. Above all, you enjoy collaborating across disciplines
and bringing structure to complex, evolving problems.
Minimum Qualifications
8+ years of experience in software engineering, ML engineering, or applied ML roles
Proficiency in Python or another modern programming language (e.g., Java, Go, Swift)
Experience building and maintaining production-grade systems
Solid understanding of machine learning concepts, especially LLMs and their
applications
Excellent communication and collaboration skills with cross-functional partners
Preferred Qualifications
Experience working on AI evaluation systems, LLM-based simulations, or agentic AI
frameworks
Background in building tools for data analysis, model evaluation, or synthetic data
generation
Familiarity with metrics instrumentation and observability in ML systems
Experience designing pipelines for AI/ML workflows
Exposure to applied research, generative models, or real-time systems
Understanding of how model quality connects to product outcomes and user
experience
Responsibilities
Design and implement systems that simulate user-like interactions and workflows,
Build tools and infrastructure to generate, manage, and analyze evaluation data
Develop scalable pipelines to extract structured insights from simulation outputs
Collaborate with scientists and engineers to instrument and assess model
performance
Engineer reusable, testable components for experimentation and evaluation workflows
Help define and operationalize success metrics aligned with product and research
goals
Eeo Content
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.
