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AIML- Software Development Engineer, Machine Learning Platforms & Infrastructure

San Francisco, United Statesfull_timeVerifiedPosted 9 Nov 2024

💰 $378,700/yr($207,800/yr – $378,700/yr)

About the role

Summary

Posted: Nov 9, 2024
Weekly Hours: 40
Role Number:200577016

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. The AI/ML Production Engineering team is looking for an exceptional Lead Systems Engineer / Systems Architect with experience in Machine Learning (ML) infrastructure services and applications. This engineer will work with global teams focussing on projects for ML compute Platforms and model lifecycles. This engineer will be a qualified technical leader with a proven track record who is able to identify and interpret problems from frontend of customer stories, to back end infrastructure in a multi-cloud environment. This engineer will be able to identify and solve scaling issues for a variety of AIML focussed services. This individual will have the opportunity to design and to build architectural solutions through cross-organizational collaboration, accurately addressing requirements, and solving complex problems. This role has high impact and is essential to creating the highest quality user experience that Apple is known for. Be an influential part of Apples “Surprise and Delight”.

Description

The position will require the following, through collaboration with team members in US and around the world. * Being embedded into the effort of supporting internal customers of ML platforms and tools, improve development velocity of software organizations who are building models for Apple Intelligence, and respond to interruptions or delays caused by failure or misses at different levels - helping to improve existing systems and designing for for future solutions in a multi cloud environment * Create performance profile for ML platforms and services, defining key performance indices (KPIs) at variety of granularity and driving the engineering implementation and deployment for the visibility of KPIs * Design and/or enhance automation of operations for infrastructure and platforms * Analyze and dig into network, load balancing, and through-put issues to help design improvements * Being closely engaged with platform and compute infra engineering teams to improve reliability of systems through enhancing operational stacks for the cloud infra and observability. * Working with Apple Infrastructure teams to improve infrastructure primitives across environments

Minimum Qualifications

* Ability for identifying problems in depth, on your own with partner teams
* Design level understanding of system architecture and large-scale service or computational platform operations
* Proficiency in coding with scripting and programming languages - (including but not limited to Bash, Python, Golang, Rust ) and have the ability to select the proper language to solve a the problem at hand
Knowledge of ML training platforms dependency on data infrastructure and networking, including intra-datacenter and cross-GPU interconnectivity technologies
Very high level Networking knowledge and practical application across multiple cloud environments
Proven high level communication experience from engineers to executives
Demonstrable team lead / management experience
15+ years of software development for platform operations or operational stack componenets, commensurate with running cutting-edge hybrid cloud services

Preferred Qualifications

Demonstrated understanding on service level management, covering aspects of configuration, security, performance, troubleshooting and usage accounting, driven by quantified KPIs
Demonstrated ability and passion to deep-diving into problems, quickly and accurately finding the path of collecting data, aggregating