Senior Software Engineer

Apple Inc.; Cupertino (CA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Stock programs

Medical and dental coverage

Tuition reimbursement

Relocation assistance

Discounted products

Job summary

Apple Inc. seeks a skilled ML/AI evaluation engineer in Cupertino to build and scale evaluation systems that shape Siri. You will develop tooling and harnesses, connect real user feedback, and advance data science rigor across iOS, iPadOS, macOS, watchOS, and visionOS.

You will collaborate across engineering, infra, and product teams, translating ambiguous requirements into measurable system behavior and robust instrumentation for production use.

Qualifications

• MS or BS in CS/ML or related field, or equivalent experience.
• Strong programming in Swift, C++, or Objective-C plus Python.
• Experience with backend/API development and production debugging.

Responsibilities

• Support evaluation of new Siri features and interaction modalities from early requirements toward automated coverage.
• Instrument product, build eval harnesses, and create test datasets from real user workflows.
• Build and improve reward models and alignment signals to measure Siri responses against user needs.
• Design and ship evaluation tooling, pipelines, and architecture end-to-end, with observability and reproducibility.
• Diagnose failures across the stack and drive durable fixes with cross-functional teams.

Skills

Swift

C++

Objective-C

Python

Data structures

Algorithms

API development

Cross-team collaboration

Education

MS/B.S. in CS/ML or related field

Tools

PyTorch

Hugging Face

Job description

Cupertino, California, United States Machine Learning and AI

As part of the Siri organization, you will build the systems and tooling that make evaluation a first-class part of how Siri is developed — not an after-the-fact check — spanning human evaluation, real user feedback, reward and alignment signals, and data science rigor across iOS, iPadOS, macOS, watchOS, and visionOS. This is a rare opportunity to work at the intersection of software engineering and rigorous evaluation science — applying machine learning engineering techniques, from model evaluation to reward modeling, to build the infrastructure that keeps this quality signal trustworthy. What you build will directly shape the direction of one of the world's most widely used assistants.

Description

In this role you'll contribute across several interconnected work streams spanning evaluation quality, reward/alignment signals, and data science. A core part of the job is bringing "evals first" thinking to the team — building tooling and harnesses grounded in real workflows, and designing for observability and reproducibility so quality can be measured clearly and issues caught early. This is a largely unexplored space with few established playbooks, so being self-driven is a must — you'll define your own path as much as execute one. Scope and priorities will evolve, and we're looking for someone who moves fluidly across these areas, bringing strong software engineering fundamentals with enough ML/LLM depth to build and ship AI-facing tooling

Responsibilities

• Supporting the evaluation of new Siri features and interaction modalities, working from ambiguous early requirements toward concrete, automated coverage
• Turning product goals into measurable system behavior — instrumenting the product, building eval harnesses, and creating test datasets grounded in real user workflows
• Building and improving reward models and alignment signals that measure whether Siri responses meet user needs
• Designing and shipping evaluation tooling, pipelines, and architecture end-to-end — from data ingestion through scoring to monitoring in production — with an eye toward observability, logging, and reproducibility
• Diagnosing failures across the stack, from environment provisioning through pipeline execution to scoring — enabling auto-diagnostics and driving durable fixes by partnering across engineering, infrastructure, and program teams to align on interfaces, priorities, and shared standards

Minimum Qualifications

• Strong programming skills in one or more compiled languages (Swift, C++, or Objective-C)
• Strong Python skills and solid computer science fundamentals, including data structures, algorithms, and clean, testable code
• Ability to quickly learn and adapt to evolving technologies and tools, such as GenAI-assisted coding, new ML frameworks, and emerging LLM/agent tooling
• Experience with backend/API development and production debugging
• Excellent communication and cross-team collaboration skills, with experience working effectively within large, cross-functional organizations
• M.S. or B.S. in Computer Science, Machine Learning, or a related field (or equivalent experience)

Preferred Qualifications

• Experience evaluating ML, LLM, or agent-based systems, including familiarity with metrics, scoring methodology, trajectory and outcome analysis, and techniques like prompting, RAG, or LLM as judge
• Understanding of reinforcement learning and the underlying techniques behind modern LLMs (e.g. transformer architectures, RLHF/RLAIF, fine-tuning, reward modeling ) and frameworks such as PyTorch or Hugging Face, as applied to evaluation and reward signal design
• Familiarity with eval-driven development — defining success criteria and test cases from product goals and real user workflows rather than abstract benchmarks
• Experience with data science methods applied to quality measurement — defining ground truth, measuring inter-rater agreement (e.g. Cohen's/Fleiss' kappa), and validating automated scorers using basic statistical techniques (e.g. correlation, confidence intervals, hypothesis testing)
• Experience with MLOps, deployment, and test/eval environment management — containerization, CI/CD, model versioning, monitoring, cloud platforms (AWS, GCP, or similar), and staging or provisioning environments to produce repeatable, deterministic conditions
• Comfort communicating and collaborating effectively across multicultural teams and time zones

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 $184,700 and $324,800, 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.

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. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Apple accepts applications to this posting on an ongoing basis.