Description

We’re building the next generation of AI evaluation systems — and we’re looking for a motivated early-career engineer who’s excited to work at the intersection of ML, software, and product. You’ll join a team focused on making AI systems — including LLMs and agentic AI - more measurable, testable, and trustworthy in real-world scenarios. This is a hands-on, collaborative role ideal for someone with a strong foundation in software engineering and machine learning, and an eagerness to grow by building tools and systems that help evaluate advanced AI behavior at scale.

As an Applied ML Engineer on our team, you’ll help develop simulation systems, support data tooling, and contribute to evaluation workflows that improve the reliability of modern AI. You’ll collaborate closely with experienced engineers and researchers, learning how to instrument, monitor, and analyze model behavior — especially for language models and agent-style systems. This is a great opportunity for someone early in their career to work with cutting-edge AI technologies in a high-impact, supportive environment. You’ll gain experience working with large-scale ML systems, learn best practices in applied AI, and grow your skills across engineering, product, and research.

Responsibilities

• Contribute to systems that simulate interactive behaviors (including LLM-driven agents)
• Help build tools to support dataset generation and evaluation workflows
• Assist in developing pipelines for structured insights from model behavior
• Collaborate with teammates to debug and improve evaluation systems
• Write clean, testable code to support scalable and reliable infrastructure
• Learn how to define metrics that connect model behavior to real-world outcomes

Key Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field
• Strong programming skills in Python or another modern language (e.g., Java, Swift, Go)
• Basic understanding of machine learning principles
• Interest in LLMs, generative AI, or agent-based systems
• Curiosity about how to evaluate and improve real-world AI performance
• Strong collaboration and communication skills

Preferred Qualifications

• Coursework or internship experience in ML, AI systems, or applied data science
• Familiarity with training or evaluating models (even via coursework or personal projects)
• Exposure to tools like PyTorch, TensorFlow, or Hugging Face
• Interest in AI observability, behavior simulation, or synthetic data
• Passion for working cross-functionally in fast-moving, exploratory teams

Compensation and 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 $120,300 and $210,100, 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.