Human-Centered AI Evaluation Engineer

Apple Inc.; Cupertino (CA); On-site; USD 184,700 - 324,800; Full time

Job summary

Apple Inc. is seeking an Evaluation & Insights Machine Learning Engineer in Cupertino, CA to lead comprehensive model evaluations for LLMs and multimodal models, building evaluation frameworks and translating findings into actionable improvements for product and engineering teams.

You will collaborate with Data Scientists, Researchers, and Engineers to ensure AI systems are reliable, safe, and aligned with human expectations, while advancing prompt engineering, RAG strategies, and ML CI/CD

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Cognitive Science, or a related technical field

Responsibilities

• Lead Rigorous Model Evaluations: Architect and execute comprehensive evaluation suites for LLMs and multimodal models, identifying edge cases in multi-step reasoning, factuality, adversarial robustness, safety, and alignment.
• Advanced Scoring Frameworks: Develop deterministic, heuristic, and LLM-assisted evaluation frameworks (e.g., LLM-as-a-judge, reward modeling) to quantify human-perceived quality metrics (e.g., helpfulness, hallucination rates).
• Actionable Signal Extraction: Translate qualitative failure modes into quantifiable loss patterns, programmatic guardrails, and actionable data-mixture adjustments for model training and inference.
• Improve Performance: Partner with engineering teams to refine model behavior, leveraging evaluation telemetry to inform prompt engineering, Retrieval-Augmented Generation (RAG) strategies, and model fine-tuning.
• Latent Pattern Recognition: Apply advanced ML techniques (e.g., embedding-based clustering, representation learning, perturbation analysis) to systematically map error taxonomies and latent failure manifolds in model outputs.
• MLOps & Automation: Develop robust MLOps workflows to codify evaluation metrics, automate regression testing across model checkpoints, and integrate human-centric assessments into ML CI/CD pipelines.
• Distributed Evaluation Pipelines: Architect scalable, distributed inference and processing pipelines (e.g., Ray, vLLM) for high-throughput model evaluation, automated annotation, and output analysis at scale.
• Human-Centric Metrics: Define quantitative evaluation frameworks that capture nuanced human factors, including trust calibration, conversational state tracking, and interpretability.
• Auto-Evaluator Systems: Build automated evaluation pipelines utilizing LLMs to assess outputs at scale, optimizing for high correlation with human baseline annotations.
• Cross-Functional Partnership: Collaborate with ML researchers, software developers, and product managers across Apple to translate product requirements into scalable, reliable, and efficient model evaluation infrastructure.

Skills

Python

PyTorch

JAX

Hugging Face

LLM evaluation

Prompt engineering

RAG architectures

Model evaluation

NLP systems

Data analysis

Education

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Cognitive Science, or a related technical field

Tools

MLflow

Weights & Biases

Job description

Apple Inc. is seeking an Evaluation & Insights Machine Learning Engineer in Cupertino, CA to lead comprehensive model evaluations for LLMs and multimodal models, building evaluation frameworks and translating findings into actionable improvements for product and engineering teams.

You will collaborate with Data Scientists, Researchers, and Engineers to ensure AI systems are reliable, safe, and aligned with human expectations, while advancing prompt engineering, RAG strategies, and ML CI/CD