AI Software Engineer

ElastixAI INC.; Seattle (WA); Hybrid; Full time

Benefits offered by this job

Comprehensive medical, dental, and vision coverage

Life insurance

Flexible Time Off (FTO)

Paid parental leave

Weekly catered lunches

Gym or fitness benefit

Job summary

A cutting-edge AI technology startup in Seattle is seeking a Systems-minded AI Software Engineer to join their core inference platform team. This role involves optimizing the AI serving platform, customizing open-source frameworks, and collaborating with engineers. Ideal candidates will have a background in systems programming, strong C++ and Python skills, and experience with LLM frameworks. The position offers competitive compensation, comprehensive healthcare coverage, and a flexible work environment.

Qualifications

• 3+ years of experience in systems programming, ML infrastructure, or distributed inference.
• Proficient in C++ and Python.
• Deep familiarity with LLM serving frameworks like vLLM or TensorRT-LLM.

Responsibilities

• Architect and extend core components of the AI serving platform.
• Customize open-source serving frameworks for model ingestion.
• Develop strategies for multi-device inference.

Skills

C++

Python

ML infrastructure

Distributed inference

Debugging

Performance analysis

Collaboration

Communication

Education

BS/MS/PhD in Computer Science, Electrical/Computer Engineering or related field

Tools

CUDA

PCIe

Docker

Kubernetes

Job description

About Elastix AI

We are building the next-gen AI inference platform.

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 building the next-generation AI inference infrastructure — co-designed across ML software and custom accelerator hardware. Our platform dynamically optimizes inference efficiency and scalability across diverse deployments, enabling adaptive, high-performance AI serving.

Role Summary

We’re looking for a systems-minded AI Software Engineer to join our core inference platform team. You’ll design and extend the low-level serving stack — hacking open-source frameworks like vLLM, SGLang, and TensorRT-LLM, building new model sharding and scheduling logic, and integrating deeply with our proprietary AI accelerator. This role sits at the intersection of ML systems, compiler/runtime engineering, and hardware-software co-design.

Key Responsibilities

• Architect, extend, and optimize core components of our AI serving platform for throughput, latency, and scalability.

• Customize open-source serving frameworks (e.g., vLLM) for proprietary model ingestion and accelerator integration.

• Develop efficient model partitioning, scheduling, and memory management strategies for multi-device inference.

• Collaborate with ML engineers on model export and runtime optimization (quantization, graph transforms).

• Work closely with hardware engineers to influence accelerator interface design and performance tuning.

• Build APIs and runtime tools enabling flexible, PyTorch-native model deployment on our infrastructure.

• Profile, debug, and optimize across the full stack — from Python orchestration to C++ kernels and PCIe drivers.

Required Qualifications

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, or related field.

• 3+ years of professional experience in systems programming, ML infrastructure, or distributed inference.

• Proficient in C++ and Python, with strong debugging and performance analysis skills.

• Deep familiarity with one or more LLM serving frameworks (vLLM, SGLang, TensorRT-LLM, DeepSpeed-Inference, etc.).

• Understanding of model deployment internals — token scheduling, KV caching, batching, and pipelined inference.

• Comfortable working close to the hardware abstraction layer — CUDA, PCIe, memory management, or runtime scheduling.

• Strong collaboration and communication skills; ability to work cross-functionally in a fast-paced startup environment.

Preferred / Bonus

• Experience with hardware-aware ML optimization, compiler/runtime integration, or accelerator SDKs.

• Hands-on experience profiling GPU/accelerator workloads.

• Familiarity with containerized deployments (Docker/Kubernetes).

• Exposure to distributed systems or large-scale inference clusters.

• Contributions to open-source ML or serving frameworks.

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 AD&D

• 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