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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Hardware Design Engineer, AI Inference Engine - **Company:** Elastixai Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Systems Engineering, Cloud Computing, Computer Engineering, Software Debugging, Distributed Systems, Hardware Design, Machine Learning, Open Source Technology, SystemVerilog, Systems Integration, Verilog, Large Language Models, Parallel Computation, Optimization Algorithms, Deployment Automation, Hardware Acceleration - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/hardware-design-engineer-ai-inference-engine-elastixai-inc-8300793 ## About the Role * BS, MS or PhD in Computer Engineering, Electrical Engineering, or a related field. * Proven experience (5+ years) in hardware design, with a strong focus on designing/implementing hardware for AI/ML acceleration. * Deep understanding of modern AI/ML models, particularly LLMs, and their computational characteristics. * Experience with hardware implementation of ML optimization techniques (e.g., sparsity, quantization, pruning). * Proficiency in Verilog or SystemVerilog for RTL design and simulation. * Strong understanding of memory system architecture, on-chip interconnects, parallel processing, and distributed computing. * Excellent problem-solving skills and the ability to analyze complex systems. * Exceptional communication and interpersonal skills, with a demonstrated ability to work effectively in a highly interdisciplinary environment, collaborating with ML, software, and cloud/systems engineers. * Ability to thrive in a fast-paced, dynamic startup environment with a strong bias for action/execution Preferred/Bonus Qualifications: * Knowledge of compiler technologies for AI models (e.g., MLIR, TVM). * Familiarity with performance modeling and analysis tools. * Experience with system-level integration and debugging. * Contributions to relevant research publications or open-source projects. * Understanding of cloud computing environments and deploying hardware accelerators in the cloud. * High-speed inter-chip networking experience ## Description We are seeking a visionary and hands-on Hardware Design Engineer to contribute to the design, definition, and implementation of our core AI inference engine. This is a deeply technical role where you will be instrumental in translating AI into a highly efficient hardware design. You will be at the center of our co-design philosophy, working to ensure our inference engine is perfectly harmonized with our ML strategies, software stack, and cloud hardware targets to deliver unparalleled performance and efficiency for next-generation AI models., * Contribute to the architectural definition, design, and implementation of a novel AI inference engine optimized for our specific ML workloads. * Collaborate closely with ML engineers to understand and influence ML directions * Work hand-in-hand with software engineers to define a seamless hardware-software interface, ensuring the inference engine is highly programmable, efficient, and easy to integrate into our broader software stack and compiler. * Partner with cloud engineers to ensure the inference engine architecture aligns with target cloud hardware capabilities, deployment strategies, and performance/cost objectives. * Model and analyze the performance, power, and area (PPA) trade-offs of different architectural choices. * Stay at the forefront of AI accelerator research, identifying emerging techniques and technologies relevant to our co-design approach. * Contribute to the RTL design, simulation, and verification efforts for the inference engine components. * Drive the hardware roadmap for the inference engine, anticipating future AI model trends and optimization opportunities. * Foster a culture of innovation and technical excellence within a highly interdisciplinary engineering team. ## Related Videos - [Green Cloud Computing](https://www.wearedevelopers.com/videos/592-green-cloud-computing) - [From Model to Metal: An Open Source Stack for Accelerating Intelligence](https://www.wearedevelopers.com/videos/1636-from-model-to-metal-an-open-source-stack-for-accelerating-intelligence) - [WebAssembly: The Next Frontier of Cloud Computing](https://www.wearedevelopers.com/videos/972-webassembly-the-next-frontier-of-cloud-computing) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML ](https://www.wearedevelopers.com/videos/78-leverage-cloud-computing-benefits-with-serverless-multi-cloud-ml) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)