Jobs: 2025 LLVM Developers' Meeting

Job Title: CPU Compiler Optimization Engineer - London, UK

Job Description: The CPU Compiler Team is seeking senior engineers passionate about working on advancing compiler performance and optimization technology. We are responsible for optimizations and code generation for CPUs on all Apple platforms. Our team works across many different organizations on state-of-the art, industry impacting technology that enhances the user experience for all Apple customers with better run-time performance, battery life, compile-times, code size or enhanced security. A lot of the team's work happens directly in the LLVM open-source project and gets presented at the LLVM Developer Meeting and the Apple’s WWDC conferences.

Job Title: CPU Compiler Backend Engineer - Herzliya, Israel

Job Description: The CPU Compiler Performance Team is seeking engineers with different levels of experience passionate about working on advancing compiler-based optimization technologies. Our team is responsible for optimizations and code generation for CPUs in all Apple platforms. We work across many different organizations on state-of-the art, industry impacting tools that enhance the user experience for all Apple customers with better run-time performance, battery life, code size, and enhanced security. A lot of the team's work happens directly in the LLVM open source project and gets presented at the LLVM Developer Meeting. Our team embodies diversity, collaboration, and creativity.

Job Title: Apple GPU Compiler Backend/Research Engineer - Cupertino, CA

Job Description: We’re looking for a skilled Compiler Backend Research Engineer to join Apple’s GPU Compiler team and help shape the future of Apple Silicon GPUs. In this role, you’ll work closely with hardware and software teams to define the GPU architecture roadmap, prototype LLVM-based compiler features, and implement performance optimizations that impact all Apple devices. You’ll collaborate with architects and micro-architects to explore new hardware capabilities, evaluate proposed changes, and drive feature development from concept to product. Your contributions will play a key role in unlocking the full potential of Apple’s GPUs across graphics and compute workloads.

Job Title: Compiler Tools Engineer - Cupertino, CA

Job Description: You’ll work on Compiler tooling for Swift, Clang and LLDB debugger on all Apple platforms, Linux, and Windows. You will make decisions about how to architect engineering, and integration workflows, considering both short- and long-term goals. Once solutions are identified, you’ll design, implement, and deploy automation and workflow changes for building, testing, and deploying the toolchain. You’ll engage with the open source LLVM and Swift communities, reducing downstream overhead by driving improvements to open-source infrastructure, tooling, and engineering workflows.

Job Title: Clang Compiler Frontend Engineer - Cupertino, CA

Job Description: We are seeking passionate compiler engineers to join the C Languages and Libraries team to advance the Clang compiler and pioneer seamless interoperability between C++ and Swift. In this role, you’ll design and implement compiler and language features in the Clang compiler to advance the stability, performance and security of Apple platforms. Additionally, you will develop innovative Swift compiler features to advance seamless interoperability between Swift and C++ languages. You will have the opportunity to drive all aspects of feature development, including planning, implementation, deployment, and communication. You will engage with and support the large, diverse user base of Clang and Swift/C++ interoperability both within Apple and externally. You will also be an active contributor to the LLVM and Swift open-source projects and collaborate with the open-source community to advance these technologies.

Job Title: Machine Learning Compiler Engineer - Cupertino, CA

Job Description: As a Machine Learning Compiler Engineer, you will:
- Work on the ANE-centric MLIR dialects, transformations and tools lowered by higher level ML framework graphs
- Architect and develop the compiler for Apple's proprietary Neural Engine Accelerator, optimizing it for deep learning inference with a focus on performance, scalability, and power efficiency
- Collaborate with cross-functional teams, including hardware and platform architecture teams, to bring new hardware silicon to market and ensure compiler support for next-gen features
- Identify and drive initiatives that will improve the scalability and general performance of AI workloads on Apple hardware, contributing to the vision and roadmap of the Apple Neural Engine team

Job Title: ML Compute Acceleration Engineer - Cupertino, CA

Job Description: Apple’s Compute Frameworks team in Graphics, Games and Machine Learning org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. Our efforts are currently focused in the key areas of linear algebra, image processing, machine learning, along with other projects of key interest to Apple. We are always looking for exceptionally dedicated individuals to grow our outstanding team to lay the foundation of technologies like Apple Intelligence.

Responsibilities:

- Adding optimizations in machine learning computation graph.
- Defining and implementing APIs in Metal Performance Shaders Graph and Metal ML Encoder, to expose new algorithms.
- Developing and maintaining our MLIR dialect in Apple and open source with upgrades using latest LLVM.
- Performing in-depth analysis, compiler and kernel level optimizations to ensure the best possible performance across hardware families.
- Tune GPU and Neural Engine accelerated compute across products.

Job Title: Swift Compiler Engineering Manager - London, UK

Job Description: The Swift Compiler Team at Apple is a unique opportunity to evolve the Swift programming language and related developer tools that shape the experience of writing Swift code. We are looking for a software engineering manager passionate about programming languages, compilers, and the developer experience. We are a fast paced and collaborative group working to improve the Swift language and compiler, and the compiler technology that provides Swift language support to IDEs and editors.

Job Title: Pre-Silicon Compute Framework Engineering Intern - Cupertino, CA

Job Description: Apple’s GPU Software team provides the graphics software foundation across all of our innovative products including iPhone, iPad, Apple TV, Mac, and Apple Watch. The Pre-silicon Frameworks team is responsible for API design and development across Metal and Metal compute frameworks and for performance analysis of upcoming hardware features in future Apple Silicon GPUs.

In this role, your focus shall be on:
- Development focused on optimizing compute kernels through utilizing upcoming hardware features.
- Performance analysis and measuring impact of the optimizations on Apple Silicon hardware.

Job Title: GPU Compiler Frontend Intern - Cupertino, CA

Job Description: Apple’s GPU Software team provides the graphics software foundation across all of our innovative products, including iPhone, iPad, Apple TV, Mac, and Apple Watch. The GPU Compiler Frontend team is responsible for Metal language design and target-independent optimizations for GPUs. In this role, you will:

- Analyze, design, and build new language constructs in MSL.
- Investigate performance and design middle-end optimizations to optimize machine learning and compute workloads.

Many LLVM-related jobs at Arm

Are you a developer looking to work with technology that reaches 100% of the connected global population?

In the past year, about 100 Arm engineers contributed to LLVM, in areas such as performance optimization, security hardening, support for new instructions and many more. We contribute to most LLVM projects, including the mid- and back-ends, MLIR, Clang, Flang, LLDB, compiler-rt, LLD, …

Your skills and knowledge of compiler fundamentals, and your passion to learn from and contribute to the LLVM community will help us develop innovative technologies that improve the performance and security of the entire field of computing.

Arm always has a range of LLVM-related job vacancies open.

Job Title: Mojo Libraries Engineer

Job Description: At Modular, we're on a mission to make AI accessible to everyone. As a Mojo Libraries
Engineer, you'll help realize this vision by shaping the foundational libraries of the
Mojo programming language. Mojo combines performance and expressiveness to
unlock the full potential of modern hardware for AI. In this role, you'll design and
implement core abstractions across the Mojo Standard Library and kernel libraries —
empowering developers to build efficiently, integrate with AI systems, and accelerate
innovation across the AI stack.

Job Title: Lead AI Graph Compiler Engineer

Job Description: At Modular, we’re on a mission to revolutionize AI infrastructure by systematically rebuilding
the AI software stack from the ground up. Our team, made up of industry leaders and experts,is building cutting-edge, modular infrastructure that simplifies AI development and
deployment. By rethinking the complexities of AI systems, we’re empowering everyone to
unlock AI’s full potential and tackle some of the world’s most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a real
difference in people’s lives, we want you on our team. You can read about our culture and
careers to understand how we work and what we value.

Job Title: MAX Platform Tooling Engineer

Job Description: At Modular, we’re on a mission to revolutionize AI infrastructure by systematically
rebuilding the AI software stack from the ground up. Our team, made up of industry
leaders and experts, is building cutting-edge, modular infrastructure that simplifies
AI development and deployment. By rethinking the complexities of AI systems, we’re
empowering everyone to unlock AI’s full potential and tackle some of the world’s
most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a
real difference in people’s lives, we want you on our team. You can read about our
culture and careers to understand how we work and what we value.

Job Title: GenAI Performance Engineer

Job Description: At Modular, we’re on a mission to revolutionize AI infrastructure by systematically
rebuilding the AI software stack from the ground up. Our team, made up of industry
leaders and experts, is building cutting-edge, modular infrastructure that simplifies
AI development and deployment. By rethinking the complexities of AI systems, we’re
empowering everyone to unlock AI’s full potential and tackle some of the world’s
most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a
real difference in people’s lives, we want you on our team. You can read about our
culture and careers to understand how we work and what we value.

Job Title: Principal Compiler Backend Engineer, Graviton Software

Location: Austin, TX | Cupertino, CA | Seattle, WA

Role: As a Compiler Principal Software Engineer, you will be responsible for the technical strategy and direction optimizing code generation for Arm CPU cores using GCC and LLVM. You are passionate in advancing compiler technology; you will lead the design and development of new Graviton-specific and generic Arm features, upstream them to the open-source projects, and drive initiatives across the organization. You will be working closely with PEs and VPs responsible for the hardware and firmware design. In this role, you will have the opportunity to dive deep into code generation on a CPU where we have full visibility on micro-architecture level, and shaping the future of compiler technology and CPU architecture.

Product: The AWS Graviton CPU based instances offer the best price/performance in AWS data centers, designed to deliver significant advancements in computing performance and efficiency. These instances are built end-to-end by AWS, providing us a unique opportunity to innovate and enhance how software runs in the largest data centers. For the past 2 years the majority of the new EC2 capacity is Graviton based, and it is used by over 95% of our 1,000 largest customers.

Team: The Graviton Software team is dedicated to ensuring that all software used by our customers and Amazon teams fully leverage the Graviton hardware. We lead open-source development initiatives and collaborate closely with the AWS Annapurna team to design and build sustainable hardware and software solutions.
Our goal is to optimize performance across a wide range of applications, including databases, media, rendering engines, machine learning, high-performance computing, and libraries. Since we designed and built all the hardware and software components, we have the insights for advancement in the compiler field that was previously not possible due to the fragmentation.

Job Title: Sr ML Compiler Engineer

Locations: Cupertino, Seattle

Role: As a Machine Learning Compiler Engineer III in the AWS Neuron Compiler team, you will be supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads. Architecting and implementing business-critical features, publish cutting-edge research, and contributing to a brilliant team of experienced engineers excites and challenges you. You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects. A background in compiler development is strongly preferred. A background in Machine Learning and AI accelerators is preferred, but not required. Candidates must be currently located or willing to relocate to Cupertino (preferred) or Seattle.

Product: AWS Machine Learning accelerators are at the forefront of AWS innovation and one of several AWS tools used for building Generative AI on AWS. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium delivers the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch and JAX. AWS Neuron is used at scale with customers like Anthropic, Databricks, Poolside, NinjaTech AI, Amazon Rufus, Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments.

Team: The Amazon Annapurna Labs Neuron Compiler team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and JAX, and converts them into code suitable for execution on Amazon’s custom ML ASICs. The team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide a quantum leap in performance.

Job Title: Research Internships

The Neuron Compiler accepts Machine Learning models from various frameworks (PyTorch, XLA, TensorFlow) and optimizes them to run on Neuron devices (the Trainium and Inferentia chips designed by Amazon). The compiler team also builds the NKI kernel language.

We are a growing research team that is part of the larger compiler organization, led by Daniel Kröning. We are looking for interns (enrolled in a PhD or Masters program) to join our team in Cupertino (Silicon Valley) or Seattle. Internship start dates are flexible. While most interns join us during the summer, we can host interns any time during the year.

We are looking for candidates with experience including but not limited to:

* Compiler optimizations and compiler intermediate representations
* Formal specification and verification of compilers
* Translation validation of compiler passes
* Specification, design, and implementation of domain-specific languages
* Compilers for machine learning frameworks
* Automated test case generation, compiler fuzzing

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