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

Apple

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

Apple

Emeryville, CA

·

On-site

·

Full-time

·

2w 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.

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About Apple

Apple

Apple

Public

A technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.

10,001+

Employees

Cupertino

Headquarters

$3.5T

Valuation

Reviews

4.0

10 reviews

Work Life Balance

4.0

Compensation

4.2

Culture

3.8

Career

3.5

Management

3.2

75%

Recommend to a Friend

Pros

Great coworkers and people

Excellent benefits and perks

Fast-paced and engaging work environment

Cons

High expectations and pressure

Management quality varies

Limited career progression opportunities

Salary Ranges

17,968 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0 reports

$121,979

total / year

Base

-

Stock

-

Bonus

-

$103,682

$140,276

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Duration

28-42 weeks

Offer Rate

20%

Experience

Positive 20%

Neutral 40%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit