Description

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.

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

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

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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 .