Hardware Design Engineer, AI Inference Engine

ABOUT ELASTIX AI We are building the next-gen AI inference platform. DESCRIPTION Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI: ElastixAI is an early-stage startup poised to revolutionize AI inference infrastructure. We are developing a cutting-edge AI inference solution that dramatically improves efficiency through a holistic co-design approach, spanning from machine learning optimizations and a highly specialized software stack to the inference engine and underlying cloud hardware. We believe in providing a customizable and optimal inference experience, much like tailoring a high-performance computing system to specific needs. Role Summary: 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. Key Responsibilities: - 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. Required Qualifications: - 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 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) - Flexible Time Off (FTO) - Paid parental leave - Company sponsored 401K Plan - Gym or fitness benefit - Commuter benefit - Investment in employee learning & development