Machine Learning Engineer - AI & ML Evaluation Frameworks

Role Number:
Team:
Hardware

Location:

Cupertino Posted:
Summary The Health Sensing Machine Learning Interpretability & Analytics (MLIA) team ensures clinical rigor and contextual trust are at the foundation of Apple’s health sensing features. We are looking for an exceptional ML Engineer to help us build the next generation of scalable evaluation infrastructure and lead rigorous investigations into model performance. You will develop cutting-edge tools, synthetic data pipelines, and automated frameworks that ensure our health features are mathematically sound, demographically equitable, and clinically safe.

If you are passionate about AI safety, robust software architecture, and pushing the boundaries of ML innovation, come join us!

Description In this role, you will architect and build large-scale evaluation frameworks to interrogate unimodal ML systems and multi-modal foundation models. Beyond infrastructure, you will lead deep-dive ML evaluations, performing failure analysis to uncover performance gaps, reasoning flaws, and edge cases. You will translate findings into actionable insights and work directly with algorithm teams to improve the safety and reliability of our health features.

Your work will empower teams across Apple to rapidly evaluate multi-modal sensor fusion while upholding Apple's privacy standards.

Minimum Qualifications BS in Computer Science, Machine Learning, Statistics, or related field3+ years of experience in ML Engineering or Applied MLStrong experience in evaluating supervised, unsupervised, LLMs and deep learning models.

Proficiency in Python with the ability to write production-grade code (OOP, CI/CD, Git)
Hands-on experience in failure analysis, evaluating LLMs and driving subsequent model improvements

Experience building data pipelines, inference frameworks, and automated evaluation systems

Strong communication skills to articulate complex technical concepts across technical and non-technical audiences

Preferred Qualifications MS/PhD in Computer Science, Machine Learning, Statistics, or related field

Experience evaluating LLMs or agentic systems (e.g., LLM-as-a-judge, RAG evaluation)

Experience with synthetic data generation and prompt engineering

Experience in parallel data processing (Spark, Kubernetes, Airflow) or privacy-preserving ML (Federated Learning)
Background in AI Safety, model interpretability, or adversarial testing

Interest in digital health and clinical rigor

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 $150,400 and $277,600, 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.

EEO Statement Apple is an equal opportunity…