Systems Engineer - Evaluation Engineering

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$318,400 / yr
Posted
6 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $161k
This role $250k
$104k most similar roles pay here $341k

This role pays more than 92% of similar roles. Most pay $129,281–$193,000 — the shaded band above. At the midpoint, this role pays about $250k versus about $161k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1777 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1443 roles with salary data.

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At a glance

TL;DR · Systems Engineer - Evaluation Engineering

As a Distributed Systems Engineer at the Evaluation Engineering team, you will play a pivotal role in designing and scaling the infrastructure for our Siri Agentic Evaluation Platform. Your responsibilities include architecting a distributed execution engine to handle thousands of parallel agent simulations, developing an internal developer platform with self-service tools, and building highly performant backend APIs using gRPC/REST. You will also manage data pipelines for high-volume trace ingestion, ensure immutable data lineage, and implement deep observability features like distributed tracing and alerting. The role requires expertise in Python (asyncio), Java, PostgreSQL, Kafka, Kubernetes, and Terraform, as well as experience with cloud-native architecture and CI/CD practices. This position addresses the challenge of scaling evaluation processes across billions of tokens and complex data types, ensuring deterministic, fault-tolerant, and cost-efficient systems.

What you'll do

  • Design and scale the core asynchronous engine for orchestrating parallel agent simulations.
  • Build self-service infrastructure and CLI tools for ML teams to integrate evaluation pipelines.
  • Create highly performant, type-safe APIs for serving complex evaluation pipeline data.
  • Construct robust data pipelines with immutable lineage for granular error tracing.
  • Implement deep observability across the platform using distributed tracing and metrics.
  • Design smart scheduling layers to prevent downstream API rate-limiting or cluster failures.

What we're looking for

  • MS in computer science or equivalent degree
  • 7+ years of experience as a distributed systems engineer
  • Strong proficiency in concurrency-focused languages like Python (asyncio) or Java
  • Deep expertise in designing robust production APIs using gRPC/Protobuf, GraphQL, or REST
  • Experience with cloud-native architecture and Kubernetes orchestration
  • Proficiency in infrastructure-as-code practices using Terraform

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