채용
Do you want to build the future of AI enabled observability at Apple? We're looking for an experienced AI observability engineer to design and build AI observability solutions that power Apple Intelligence, Search, and AI infrastructure powering Apple's intelligent products. We're at the forefront of building AI-first observability services, blending AI, cloud-first engineering, and industry standards to deliver smart, scalable solutions. Your work will directly impact the experience of billions of users on their favorite Apple devices. If you are a seasoned principal or senior software engineer with a proven track record in building AI enabled observability solutions and have a deep passion for observability, AI, cloud-native technologies and large-scale distributed systems, we want to talk with you.
Description
We're pioneering the next generation of AI-powered observability solutions. While we innovate to build new solutions, we also leverage industry-standard open-source technologies. In this role, you will collaborate with a team of engineers to lead the design and development of user-facing observability features for AIML products and infrastructure. You will also be responsible for providing technical guidance, sharing observability best practices and know-how, leveraging AI pipelines and mentoring the team to develop and deliver best-of-class features and a delightful user experience for all users.
Preferred Qualifications
Knowledge of current Gen AI research and techniques in the following areas: MCPs, RAG systems, Agentic AI (multi-agent orchestration, tool calling)
Hands-on experience with agentic AI frameworks (e.g. Lang Graph, Auto Gen, CrewAI) for building multi-step reasoning and tool-using agents
Demonstrated experience in building observability systems for metrics, distributed tracing, logs, profiling and in building observability data collection using Open Telemetry
Demonstrated proficiency in AWS services such as EKS and native Kubernetes, storage such as S3, networking, database and observability services
Experience with large scale observability visualization systems with knowledge of popular visualization tools like Grafana, Data Dog, and ELK
Proficiency using cloud-native software development tools including coding, CI/CD and testing frameworks
Building large-scale incident management, alert management and notification systems
Active open source project contributions is a plus
Minimum Qualifications
7+ years of experience in building ML pipelines, portable workflows and in model tuning to deploy ML and LLM models in production for customer-facing features
7+ years software engineering experience and strong background in computer science: distributed systems, algorithms and data structures, APIs and highly-scalable, reliable systems and micro-services
Demonstrated experience using LLM and ML models for AIOps and model observability
Demonstrated experience using LLMs, ML frameworks i.e. Tensor Flow, Py Torch and libraries like Scikit-learn, Num Py, Lang Chain, MLFlow, Kube Flow
Demonstrated experience in delivering well-architected, reliable, highly-scalable cloud-native distributed systems for data management, observability or analytics services
Strong software engineering experience in design, development and testing in cloud-native environments
Strong coding skills in Python, Go, Javascript, Java
Demonstrated experience in building large-scale micro-services using public cloud infrastructure and/or "private cloud" environments
Experience developing intelligent detection and resolution features for incident management, automated remediation and root cause analysis
Excellent verbal and written communication skills with strong problem solving skills
Excellent interpersonal skills for collaborating across teams, stakeholders, and open source collaborators
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 $212,000 and $318,400, 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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Apple 소개

Apple
PublicApple 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
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0개 리포트
$114,215
총 연봉
기본급
$45,686
주식
$57,108
보너스
$11,422
$79,951
$148,480
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
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