Applied ML Engineer - AI/ML Evaluation & Simulation

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.

Description

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

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

Minimum 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

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 .