AI Compiler and Performance Engineer

ElastixAI INC.; Seattle (WA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive medical, dental, and vision coverage

Flexible Time Off (FTO)

Paid parental leave

Gym or fitness benefit

Weekly catered lunches in the office

Investment in employee learning & development

Job summary

A pioneering AI startup in Seattle is seeking a Software Engineer for their AI inference platform. This role focuses on optimizing hardware performance through advanced compiler work. Candidates should have a strong background in machine learning frameworks and experience with compiler technologies. The position offers a hybrid work model, where innovative solutions can be developed in a supportive environment. Join a team committed to pushing AI technology to new limits.

Qualifications

• Deep experience building compilers, optimizing kernels, or working with ML frameworks.
• Proficiency in programming languages such as Python and C++.
• Understanding of LLM architectures and transformer internals.
• Experience with GPU/TPU/FPGA/ASIC compute models.
• Familiarity with GPU/TPU/FPGA compute models and memory hierarchies.
• Understanding of quantization and sparsity for deep learning.
• Experience with ML frameworks (PyTorch, TensorFlow, JAX).
• Strong software engineering fundamentals and testing.

Responsibilities

• Decompose LLM operations into efficient kernel primitives.
• Implement IR transformations and optimizations for novel hardware.
• Collaborate with ML researchers on algorithmic optimizations.
• Develop performance models and profiling tools.
• Build performance models, profiling tools, and benchmarking frameworks to identify bottlenecks.
• Prototype improvements across the stack from PyTorch/XLA passes to custom kernels.
• Contribute to shaping the overall system architecture of a first-of-its-kind inference engine.

Skills

Compiler building

Kernel optimization

Machine Learning frameworks

Python

C++

MLIR

GPU compute models

Quantization

Software engineering best practices

Education

BS/MS/PhD in Computer Science or related field

Tools

MLIR/LLVM/XLA/TVM

GPU/TPU/FPGA/ASIC models

PyTorch/TensorFlow/JAX

Profiling & benchmarking tools

Job description

Description

Job Title: Software Engineer, AI Inference Platform

Company: ElastixAI, Inc.

Location: Seattle, WA (Hybrid - 3 days/week in office)

About ElastixAI

ElastixAI is an early-stage startup on a mission to reinvent AI inference infrastructure from the ground up. We’re building a next-generation inference platform that delivers unprecedented efficiency by tightly integrating machine learning, software stack, and custom hardware. Our philosophy is simple: the best performance comes from holistic co-design, where every layer, from model architecture to kernels to silicon, works in harmony. If you’re excited about pushing AI performance to physical limits, and about shaping the future of large-scale inference, we’d love to meet you.

Role Summary

We are looking for a deeply technical AI Compiler & Performance Engineer who thrives at the intersection of ML, compilers, and hardware. In this role, you will design how LLM operations decompose into highly efficient proprietary kernel primitives, optimize execution pipelines, and co-develop abstractions with our hardware and ML teams. This is not a “typical” compiler role, it’s a chance to rethink the entire AI compute stack. At ElastixAI, if improving inference efficiency requires inventing new quantization schemes, rethinking graph-level optimizations, or modifying the hardware ISA, we do it. You’ll have end-to-end ownership to explore radically new ideas and make them real.

Key Responsibilities

• Break down LLM and transformer workloads into fine-grained primitives tailored to our proprietary compute hardware.
• Design and implement IR transformations, graph optimizations, kernel lowering, and code generation for novel hardware architectures.
• Collaborate with ML researchers to co-design algorithmic optimizations that yield real end-to-end performance gains.
• Work closely with hardware architects to refine microarchitectural features, instruction sets, memory hierarchies, and execution models.
• Build performance models, profiling tools, and benchmarking frameworks to identify bottlenecks and guide design decisions.
• Prototype and validate improvements across the entire stack — from PyTorch/XLA-level passes to custom kernel implementations.
• Contribute to shaping the overall system architecture of a first-of-its-kind inference engine.

Required Qualifications

• BS/MS/PhD in Computer Science, Software Engineering, or a related field.
• Deep experience building compilers, optimizing kernels, or working with ML frameworks at a systems level.
• Strong proficiency in one or more programming languages such as Python and C++.
• Strong understanding of one or more of the following:
• LLM architectures and transformer internals
• MLIR, LLVM, XLA, TVM, Triton, or similar compiler infrastructures
• GPU/TPU/FPGA/ASIC compute models, memory hierarchies, and parallel execution
• Quantization, sparsity, or algorithmic optimization for deep learning
• Deep expertise on ML frameworks (e.g., PyTorch, TensorFlow, JAX) and understanding of ML model deployment challenges.
• Solid understanding of software engineering best practices, including data structures, algorithms, and testing.
• Thinking in terms of latency, cycles, memory bandwidth, and arithmetic intensity, not just algorithms.
• Excellent problem-solving abilities and a knack for tackling complex technical challenges.
• Excited to collaborate across ML, hardware, and software boundaries to invent something fundamentally new.
• Strong communication skills and a proven ability to collaborate effectively in a cross-functional team environment.
• Ability to thrive in a fast-paced, dynamic startup environment.

Preferred / Bonus

• PhD in Computer Science, Software Engineering, or a related field.
• Experience with custom hardware accelerators for ML inference.
• Contributions to open-source compiler or ML systems projects.
• Prior startup experience or background building first-generation systems.

What We Offer:

• A chance to be a foundational engineer in an innovative AI startup
• A dynamic and collaborative work environment and the change to have a significant impact on new technology
• The opportunity to work on challenging problems at the intersection of ML, software, and systems.
• Competitive compensation and startup equity package
• Comprehensive medical, dental, and vision coverage (100% paid by employer)
• Life insurance and ADDD
• Flexible Time Off (FTO)
• 12-paid holidays
• Paid parental leave
• Gym or fitness benefit
• Commuter benefit
• Weekly catered lunches in the office
• Investment in employee learning & development