--- title: 'Architecture Modeling Engineer at Mythic' canonical: 'https://feeny.ai/job/architecture-modeling-engineer-mythic-austin-26a16nzpaanw' type: 'job' last_seen: '2026-09-07' --- # Architecture Modeling Engineer at Mythic - **Company:** Mythic - **Location:** Austin, TX - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2025-09-03 - **Last confirmed live:** 2026-09-07 - **Apply:** https://jobs.lever.co/mythic-ai.com/28b62290-688c-44f4-b4db-008af6607533 ## Job description We’re hiring experienced Architecture Modeling Engineers from junior to senior levels to play a key role in developing the designs that will bring our next-generation AI processors to life. About Us: Mythic is building the future of AI computing with breakthrough analog technology that delivers 100× the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications - whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from –40 °C to +125 °C, making it ideal for industrial, automotive, aerospace, and defense. We’ve raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets. The salary range for this position is $120,000–$225,000+ annually. Actual compensation depends on experience, skills, qualifications, and location. Architecture Modeling at Mythic: At Mythic, architecture modeling is at the core of how we design and deliver breakthrough AI hardware. Our models allow us to quantify the real-world performance of new architectures—capturing critical tradeoffs in throughput, latency, and efficiency—before a single chip is built. Modeling plays a central role in active design development, predicting how AI workloads generated by the Mythic compiler will run on silicon. These models serve as a golden reference for verifying RTL implementations and enable our software teams to begin developing validation and customer-facing code long before hardware is available. Even after silicon arrives, our modeling tools remain invaluable, offering deeper insight into performance bottlenecks and guiding ongoing software optimization. ## Responsibilities - Architect and create various types of hardware models with varying goals - e.g. transaction-level, cycle-accurate. - Create or build on top of existing hardware models to simulate functionality of custom AI software. - Create prototyping models for estimating power, performance and area of new chip architectures. - Create cycle-accurate models of the hardware (C++/SystemC). - Collaborate with peer engineering teams to co-design and co-verify the hardware implementation. - Investigate new architectural ideas, many co-designed with other system components. ## Requirements - Bachelor’s, Master’s, or Ph.D. degree in Electrical Engineering, Computer Engineering, or Computer Science. - 5+ years experience required creating performance models for architectural investigations. This experience can include time spent in academic work including papers, thesis, and dissertation work. The years required can be reduced if prior modeling experience is related to systems for AI. - Academic and working knowledge of a variety of hardware concepts such as CPUs, memory systems, bus interconnects, security, chip interfaces, etc. - Proficiency and experience with C++/SystemC as used in modeling. - Proficiency and experience with hardware modeling for performance and/or power. - Strong communication skills, both written and spoken. ## About Mythic ## Company Overview - **One-liner**: Mythic is a semiconductor company developing analog compute-in-memory (CIM) processing units that deliver up to 100x greater energy efficiency for AI inference at the edge, in automotive, and in the data center. - **Entity Type**: Private (Series C; total funding $290.4M as of 2021) - **Headquarters**: Austin, Texas, United States (with offices in Silicon Valley, Vancouver, and Bangalore) - **Founded**: 2012 - **Founders**: Mike Henry, Dave Fick, and Laura Fick (co‑founder and Chief Analog Compute Architect) ## Core Business - **Primary industry**: Semiconductor manufacturing – AI hardware accelerators - **Target customers**: B2B – OEMs and system integrators in automotive, defense, robotics, industrial IoT, and enterprise data centers - **Mission statement**: “Enable a new era of AI performance and innovation by making it easier and more affordable to deploy powerful AI solutions, from the data center to the edge device.” ## Products & Services - **Mythic APU (Analog Processing Unit)**: A chip built on analog compute-in-memory architecture that stores AI model weights inside flash memory and performs computation directly at the source, eliminating the energy wasted by moving data between processor and memory. Delivers up to 100x system‑level performance‑per‑watt‑per‑dollar vs. conventional digital/GPU inference. Available today for edge and enterprise deployments. - **Mythic Software Platform**: A unified hardware/software stack that simplifies deploying AI models on the APU, including compilers, runtimes, and model optimization tools. ## Market Standing - **Valuation / Market Cap**: Not disclosed (private company) - **Key Metric**: $14.1M annual revenue (2026 estimate); $290.4M total funding raised across 8 rounds, including a $70M Series C in 2021 led by Hewlett Packard Enterprise and BlackRock, with earlier rounds led by SBVA (SoftBank) and Valor Equity Partners. - **Notable Investors / Partners**: BlackRock, Hewlett Packard Enterprise, Valor Equity Partners, SBVA (SoftBank). The team includes veterans from NVIDIA, ON Semiconductor, and Luminar. - **Growth Signals**: - Headcount grew 46.4% YoY (to ~42 employees as of 2026). - Acquired Videantis (Jan 2026), a German AI processor company whose silicon is already running in 30 million production vehicles, giving Mythic an instant automotive ADAS footprint. - Active job postings for 18 open roles across hardware, software, and corporate functions. - Expanding into India with a VP of Mythic India and a Bangalore office. ## Competitive Advantages - **Analog Compute-in-Memory**: Eliminates the Von Neumann bottleneck by computing in analog directly where data is stored, achieving up to 100x better energy efficiency than traditional digital or GPU inference. - **Automotive‑Grade from Day One**: The Videantis acquisition provides proven, scalable ADAS/AD platforms already deployed in millions of vehicles, with customers like Bosch, Continental, and Valeo. - **Proven Silicon**: Mythic’s APU is operational and available today, not theoretical. - **Deep Talent Pool**: Team includes experts from NVIDIA, ON Semiconductor, Cisco, and leading chip companies, with a strong mix of analog, digital, and AI expertise. ## Strategic Focus - **Scale the Automotive Business**: Leverage the Videantis acquisition to become a major player in automotive ADAS and autonomous driving compute. - **Expand into Defense and Industrial**: Target high‑reliability, low‑power AI applications in defense, robotics, and industrial IoT. - **Data Center Edge**: Deliver efficient inference for enterprise AI workloads that cannot afford the power cost of traditional GPUs. - **Grow Global Team**: Build out software, hardware, and field engineering teams, particularly in India and the U.S. ## Why Work Here - **Impactful Mission**: Work at the frontier of AI hardware, solving the fundamental energy efficiency problem in AI compute. - **Collaborative, Results‑Focused Culture**: Mythic describes itself as a “collaborative, results‑focused team where everyone has a chance to contribute and lead.” - **Rapid Growth**: 46% YoY headcount growth and a recently acquired company signal strong momentum and career growth opportunities. - **Diverse Technical Challenges**: Roles span chip design, compiler engineering, AI algorithms, firmware, and systems engineering. - **Hybrid/Office Policy**: Some roles are listed as hybrid (e.g., Palo Alto, Austin) or fully on‑site; exact policy varies by position. The company has offices in Austin, Silicon Valley, and Vancouver, with a growing presence in Bangalore. - **Notable Perks**: Not explicitly stated, but working at a well‑funded, pre‑IPO startup in the AI hardware space typically offers equity, competitive compensation, and the chance to shape the future of computing. ## Sources 1. [Mythic Official Website](https://www.mythic.ai/) 2. [Mythic Careers Page (Lever)](https://jobs.lever.co/mythic-ai.com) 3. [Mythic Team Page](https://www.mythic.ai/company) 4. [Mythic LinkedIn Company Profile](https://www.linkedin.com/company/mythic-ai) 5. [Mythic Join Us Page](https://mythic.ai/join-us/) ## Other roles at Mythic - [Principal Camera & Sensor Applications Engineer](https://feeny.ai/job/principal-camera-sensor-applications-engineer-mythic-palo-alto-a9nhp5ykhgfs) — Palo Alto, CA - [EDA / CAD Engineer](https://feeny.ai/job/eda-cad-engineer-mythic-austin-qh2yvm2prd5z) — Austin, TX - [Director, IT & DevOps](https://feeny.ai/job/director-it-devops-mythic-palo-alto-0fseadctweac) — Palo Alto, CA - [System Administrator](https://feeny.ai/job/system-administrator-mythic-hannover-59km42a7bh8t) — Hannover, Germany - [Senior NVM Digital Designer](https://feeny.ai/job/senior-nvm-digital-designer-mythic-palo-alto-a7mj1swqer36) — Palo Alto, CA - [Senior Mixed Signal / Memory Circuit Designer](https://feeny.ai/job/senior-mixed-signal-memory-circuit-designer-mythic-palo-alto-4ed9jh7cdyzy) — Palo Alto, CA - [Senior NVM Designer](https://feeny.ai/job/senior-nvm-designer-mythic-palo-alto-s3bjnvzh9evy) — Palo Alto, CA - [Executive Assistant & Office Manager (Bangalore)](https://feeny.ai/job/executive-assistant-office-manager-bangalore-mythic-bengaluru-0nhckgpaxfjh) — Bengaluru, India - [VP, Marketing](https://feeny.ai/job/vp-marketing-mythic-palo-alto-v62apd0f3aw9) — Palo Alto, CA - [VP, Systems Engineering](https://feeny.ai/job/vp-systems-engineering-mythic-palo-alto-q74kcbvb8adp) — Palo Alto, CA