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Senior/Staff Applied ML Engineer - AI/ML Evaluation & Simulation

Apple

Senior/Staff Applied ML Engineer - AI/ML Evaluation & Simulation

Apple

Seattle, WA

·

On-site

·

Full-time

·

2d ago

We're building the next generation of AI evaluation systems - and we're looking for a hands-on engineer who can bridge ML, software, and product to make AI systems more measurable, testable, and trustworthy.

We're part of the AI/ML Evaluation organization, seeking a Senior or Staff-level Applied ML Engineer with strong software engineering skills and a solid understanding of machine learning. In this hands-on role, you'll help design and build intelligent systems that simulate complex interactions (including agentic workflows powered by LLMs), develop tools for extracting structured insights, and create robust evaluation datasets.

You'll also contribute to building scalable platforms for simulation and behavior analysis. This role sits at the intersection of ML, engineering, and product - ideal for someone passionate about bringing clarity and rigor to real-world AI performance.

Description

We're looking for a pragmatic engineer who thrives at the intersection of machine learning and software development - capable of building robust, scalable systems that support evaluation and development of advanced AI capabilities, including large language models and agentic behaviors.

A successful candidate is comfortable navigating ML, systems, and product domains.

You bring strong software engineering fundamentals, experience building and maintaining end-to-end pipelines, and a practical understanding of how to evaluate AI systems in real-world contexts. You're curious about how LLMs behave in interactive or agentic settings, thoughtful about evaluation design, and eager to build tools that improve visibility and trust in AI. Above all, you enjoy collaborating across disciplines and bringing structure to complex, evolving problems.","responsibilities":"Design and implement systems that simulate user-like interactions and workflows

Build tools and infrastructure to generate, manage, and analyze evaluation data

Develop scalable pipelines to extract structured insights from simulation outputs

Collaborate with scientists and engineers to instrument and assess model performance

Engineer reusable, testable components for experimentation and evaluation workflows

Help define and operationalize success metrics aligned with product and research goals

Preferred Qualifications

Experience working on AI evaluation systems, LLM-based simulations, or agentic AI frameworks

Background in building tools for data analysis, model evaluation, or synthetic data generation

Familiarity with metrics instrumentation and observability in ML systems

Experience designing pipelines for AI/ML workflows

Exposure to applied research, generative models, or real-time systems

Understanding of how model quality connects to product outcomes and user experience

Minimum Qualifications

8+ years of experience in software engineering, ML engineering, or applied ML roles

Proficiency in Python or another modern programming language (e.g., Java, Go, Swift)

Experience building and maintaining production-grade systems

Solid understanding of machine learning concepts, especially LLMs and their applications

Excellent communication and collaboration skills with cross-functional partners

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 .

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 $171,600 and $302,200, 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.

총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Apple 소개

Apple

Apple

Public

Apple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.

10,001+

직원 수

Cupertino

본사 위치

$3.5T

기업 가치

리뷰

3.9

10개 리뷰

워라밸

2.5

보상

4.2

문화

3.8

커리어

3.5

경영진

3.2

72%

친구에게 추천

장점

Great benefits and compensation

Talented colleagues and supportive teams

Learning opportunities and mentorship

단점

Work-life balance challenges

High stress and pressure

Fast-paced environment

연봉 정보

11,365개 데이터

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0개 리포트

$121,979

총 연봉

기본급

-

주식

-

보너스

-

$103,682

$140,276

면접 경험

3개 면접

난이도

3.3

/ 5

소요 기간

28-42주

합격률

33%

경험

긍정 33%

보통 0%

부정 67%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience