Senior Full-Stack Engineer - Web Platforms for ML Inference
Apple's AIML organization powers intelligence across many of our most iconic experiences. Within AIML, the Annotation AI Services organization builds the foundational systems that enable large-scale model inference, data pipelines, and ML platform capabilities for annotation platforms.
We are looking for a Senior Full-Stack Engineer who enjoys working across modern web applications and cloud-native backend systems. This role is ideal for engineers who value end-to-end ownership-from designing polished, scalable React + TypeScript web platforms to building and operating the cloud infrastructure and services that power them.
You will focus on web platforms used by annotation platforms and operation teams across Apple to discover, configure, and interact with inference services, pipelines, and ML infrastructure-helping make complex systems accessible, reliable, and scalable.
Description
As a Senior Full-Stack Engineer on the Annotation AI Services team, you will design and build web platforms that sit at the front door of ML inference and pipeline systems.
You will create modern, high-quality React and TypeScript applications while also developing cloud-native backend services deployed on AWS and Kubernetes. The role values engineers who appreciate working across the stack and who enjoy collaborating closely with infrastructure, ML systems, and platform teams to deliver cohesive, end-to-end solutions.","responsibilities":"Design, build, and maintain modern web applications using React and TypeScript.
Own frontend architecture, including:
Component and state management patterns
Performance, scalability, and responsiveness
Secure and reliable API integrations
Build web platforms that enable teams to:
Discover and configure inference services
Interact with ML pipelines and workflows
Monitor usage, health, and operational signals
Establish best practices around testing, maintainability, accessibility, and developer experience.
Design and implement backend endpoints that power the product UI, with clear API contracts and pragmatic versioning/backward compatibility (REST and/or gRPC).
Build reliable services in Python and/or Node.js with basic correctness patterns: input validation, auth checks, pagination, idempotency where needed, and sensible error handling.
Work effectively in a Kubernetes + AWS environment: read logs/metrics, debug issues, and make safe, incremental changes to services that run on EKS (or equivalent).
Security basics: service-to-service auth (OIDC/JWT/IAM patterns used internally), least-privilege mindset, and safe handling of secrets/config.
Data integration for product features: use common persistence/messaging building blocks (e.g., DB + S3 + queue) and work within existing schema/migration workflows.
Preferred Qualifications
Experience building internal platforms or developer-facing tools.
Familiarity with ML platforms, inference systems, or data pipelines.
Experience with gRPC and/or Protobuf-based APIs.
Exposure to observability systems (metrics, logging, tracing).
Experience operating services in production Kubernetes environments.
Experience with safe rollout strategies (e.g., canary or blue/green), autoscaling, and Kubernetes resource tuning (requests/limits).
Experience with performance and cost optimization: load/perf testing, caching strategies, capacity planning, and rate limiting/quotas.
Experience designing/operating persistence and messaging patterns (e.g., DB + queues + object storage), including schema migrations and reliability patterns (retries/DLQs).
MS in Computer Science or related field.
Minimum Qualifications
5+ years of professional software engineering experience.
Strong experience building and shipping production web applications with React and TypeScript (including testing and performance).
Working backend experience with Python and/or Node.js building APIs and integrations used by frontend applications.
Experience shipping and debugging services in a cloud environment (AWS preferred) and a containerized runtime (Kubernetes/EKS or equivalent preferred).
Experience designing and consuming APIs for frontend-backend integration (REST and/or gRPC), including auth, pagination, and error handling.
Solid fundamentals in web architecture and security (authentication/authorization and secure API design).
Comfortable working across the stack and collaborating with product/design/backend/infrastructure partners.
BS in Computer Science or equivalent practical experience.
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 .
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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 $147,400 and $272,100, 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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