Machine Learning Engineer - AI & ML Evaluation Frameworks

Apple Inc.; Cupertino (CA); On-site; USD 147,400 - 272,100; Full time

Benefits offered by this job

Comprehensive medical and dental coverage

Retirement benefits

Discounted products and free services

Job summary

Apple Inc. is seeking an exceptional ML Engineer to join the Health Sensing Machine Learning Interpretability & Analytics team in Cupertino, California. The role involves developing scalable evaluation tools and ensuring model performance and safety for health sensing features.

Candidates should possess a BS in Computer Science or a related field, alongside 3+ years of experience in ML Engineering. A strong proficiency in Python and experience in failure analysis and data pipelines are essential. Apple offers a competitive compensation package and various employee benefits.

Qualifications

• 3+ years of experience in ML Engineering or Applied ML.
• Strong experience in evaluating supervised, unsupervised, LLMs and deep learning models.
• Experience building data pipelines, inference frameworks, and automated evaluation systems.
• Hands-on experience in failure analysis.

Responsibilities

• Design robust methodologies and scalable frameworks to assess model performance.
• Drive failure analysis and build instrumentation for clinical hallucinations.
• Develop tools to discover biases and measure demographic equity.
• Translate evaluation results into actionable insights for researchers.

Skills

Python

Machine Learning

Deep Learning

Failure Analysis

Data Pipelines

Communication Skills

Education

BS in Computer Science or related field

Tools

Kubernetes

Spark

Airflow

Job description

Cupertino, California, United States

Hardware

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.

Responsibilities

• Design robust methodologies and scalable frameworks to assess the performance, reliability, and safety of both traditional ML and foundation models (e.g., LLMs, diffusion models).
• Drive failure analysis along with building instrumentation to detect clinical hallucinations, reasoning flaws, and edge cases.
• Expand LLM/diffusion‑based data generation pipelines that enable model training and evaluation without exposing real user data.
• Build data adaptors and visualizers to fuse asynchronous time‑series signals (wearables, camera, behavioral metadata).
• Develop generalizable tools and metrics to discover biases and measure demographic equity across diverse populations.
• Translate evaluation results into actionable engineering insights for GenAI researchers, algorithm leads, and clinical experts.

Minimum Qualifications

• BS in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of experience in ML Engineering or Applied ML.
• Strong 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.

Compensation & Benefits

Base pay for this role is between $147,400 and $272,100, based on skills, qualifications, experience, and location. Employees may also participate in discretionary stock awards, purchase Apple stock at a discount, and receive discretionary bonuses or commission payments. Benefits include comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and reimbursement for certain educational expenses (including tuition). Relocation may be considered for eligible candidates.

Eligibility & Diversity

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.

At Apple, we believe accessibility is a fundamental human right. By welcoming as many perspectives as possible, we help you build a career where you feel you belong.

Additional Information

Learn about accessibility in Apple’s workplace. Learn about reasonable accommodations for job applicants. Apple accepts applications to this posting on an ongoing basis.