Evaluation & Insights Machine Learning Engineer
Job Description
Work on Apple’s Human-Centered AI team to evaluate and improve AI systems using data science, model behavior analysis, and qualitative insights.
- Architect and execute comprehensive evaluation suites for LLMs and multimodal models, surfacing edge cases in multi-step reasoning, factuality, adversarial robustness, safety, and alignment
- Build deterministic, heuristic, and LLM-assisted evaluation frameworks (including LLM-as-a-judge and reward modeling) to quantify human-perceived quality metrics such as helpfulness and hallucination rates
- Convert qualitative failure modes into quantifiable loss patterns, programmatic guardrails, and actionable data-mixture adjustments for both training and inference
- Partner with engineering teams to refine model behavior using evaluation telemetry to guide prompt engineering, Retrieval-Augmented Generation (RAG) strategies, and model fine-tuning
- Apply advanced ML techniques (embedding-based clustering, representation learning, perturbation analysis) to map error taxonomies and latent failure manifolds
- Develop robust MLOps workflows to codify evaluation metrics, automate regression testing across model checkpoints, and integrate human-centric assessments into ML CI/CD pipelines
- Design scalable, distributed inference and processing pipelines (for example, Ray and vLLM) to support high-throughput evaluation, automated annotation, and large-scale output analysis
- Define quantitative evaluation frameworks capturing nuanced human factors such as trust calibration, conversational state tracking, and interpretability
- Build automated evaluation pipelines that use LLMs to assess outputs at scale, with optimization for high correlation to human baseline annotations
- Collaborate across Apple with ML researchers, software developers, and product managers to translate product requirements into reliable and efficient evaluation infrastructure
Requirements
- Knowledge of human factors, HCI, or cognitive science methodologies as applied to AI system design
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Cognitive Science, or a related technical field
- 8+ years of relevant industry experience in ML Engineering or Applied Research
- Advanced proficiency in Python and modern deep learning ecosystems (PyTorch, JAX, Hugging Face)
- Proven experience building scalable ML inference pipelines, model-evaluation workflows, and structured rating frameworks for large-scale AI systems
- Strong ability to interpret unstructured model outputs (text, transcripts, embedding spaces) and synthesize qualitative findings into actionable engineering guidance and training objectives
- Hands-on experience developing, fine-tuning, or evaluating LLMs, multimodal models, and NLP systems
- Deep familiarity with AI quality metrics, hallucination detection techniques (for example SelfCheckGPT), model alignment (RLHF/DPO), and LLM-as-a-judge frameworks (for example G-Eval and DeepEval)
- Experience building internal tools or automated pipelines for ML workflows using tools like MLflow and Weights & Biases or similar platforms
- Strong familiarity with advanced prompt engineering, RAG architectures (vector databases, semantic search), and Fine-Tuning
Technologies
- Python
- PyTorch
- JAX
- Hugging Face
- LLM-as-a-judge
- reward modeling
- Retrieval-Augmented Generation (RAG)
- embedding-based clustering
- representation learning
- perturbation analysis
- MLOps
- CI/CD pipelines
- Ray
- vLLM
- trust calibration
- SelfCheckGPT
- RLHF
- DPO
- G-Eval
- DeepEval
- MLflow
- Weights & Biases
- vector databases
- semantic search
- Fine-Tuning
- LLM-assisted evaluation frameworks
Benefits
- Comprehensive medical and dental coverage
- Retirement benefits
- Discounted products and free services
- Reimbursement for certain educational expenses, including tuition
- Discretionary restricted stock unit awards
- Opportunity to purchase Apple stock at a discount via the Employee Stock Purchase Plan
- Base pay range between $184,700 and $324,800
- Comprehensive total compensation package may include discretionary bonuses or commission payments as well as relocation
Pay & Benefits
- Base pay range: $184,700 to $324,800 (depends on skills, qualifications, experience, and location)
- Employee stock programs: eligibility-dependent discretionary employee stock programs and Employee Stock Purchase Plan participation
- Benefits include comprehensive medical and dental coverage, retirement benefits, discounted products and free services, and tuition reimbursement for formal education related to career advancement
- This role might be eligible for discretionary bonuses or commission payments and relocation
- Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program