Manager, Machine Learning Infrastructure - SIML

Cupertino, CA, US • Posted 30+ days ago • Updated 2 hours ago
Full Time
On-site
Fitment

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Job Details

Skills

  • Writing
  • Mathematics
  • Data Processing
  • Large Language Models (LLMs)
  • Human-computer Interaction
  • Benchmarking
  • Apache Velocity
  • Collaboration
  • Interfaces
  • Roadmaps
  • Computer Science
  • Computer Engineering
  • Software Engineering
  • IT Management
  • Management
  • Python
  • Java
  • C
  • C++
  • Systems Design
  • Workflow
  • Training
  • Evaluation
  • Artificial Intelligence
  • Machine Learning (ML)
  • Computer Vision
  • Natural Language Processing
  • Productivity

Summary

Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling necessary to create these exciting technologies.

We are the System Intelligent and Machine Learning (SIML) group that provides foundational computer vision and machine learning technologies to Apple's ecosystem. Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes..). We are seeking an Engineering Manager to lead the development of scalable, high-performance infrastructure that powers product-focused machine learning initiatives.

Description

In this role you will lead a team responsible for building and operating infrastructure that enables large-scale data processing (terabytes and beyond) across domains such as image generation, large language models (LLMs), computer vision, natural language processing, human-computer interaction, and text recognition. This includes designing systems for dataset creation and management, ingesting annotated and inferred data, and delivering seamless access to high-quality data for ML researchers and engineers.

A key part of this role is driving systems that enable deeper understanding of model behavior-such as failure mode analysis, evaluation pipelines, and benchmarking frameworks-to accelerate iteration velocity and improve model quality. You will work across the stack, tackling challenges ranging from low-level distributed systems and compute efficiency to building stable, intuitive interfaces for internal users.

As a leader, you will partner closely with cross-functional teams including ML researchers, product teams, and platform engineering to define roadmaps, align priorities, and deliver impactful solutions. You will play a critical role in shaping how ML systems are developed, evaluated, and scaled from early experimentation to production.

Minimum Qualifications

Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, or a related field (or equivalent experience)

7+ years of software engineering experience, with 2+ years in a technical leadership or management role

Strong programming skills in one or more of: Python, Java, Go, C/C++

Solid understanding of machine learning fundamentals and ML system workflows

Proven experience in building and scaling distributed systems and backend infrastructure

Strong system design skills with expertise in at least one systems domain (e.g., data infrastructure, distributed systems, ML platforms)

Preferred Qualifications

Experience building infrastructure for ML workflows (data pipelines, training systems, evaluation frameworks, or deployment systems)

Domain experience in areas such as AI/ML, computer vision, NLP, or related fields

Experience working with large-scale datasets and compute-intensive systems

Experience improving developer productivity through tooling and platform abstractions

Ability to operate effectively in cross-functional, fast-paced environments with evolving requirements
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: 832ad8db78927cc67bca0d74415f3df5
  • Posted 30+ days ago
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