{"id":48907,"url":"https://alion.io/job/elastix-hardware-design-engineer-ai-inference-engine","title":"Hardware Design Engineer, AI Inference Engine","company":{"id":10106,"name":"Elastix","domain":"elastix.ai","url":"https://alion.io/company/elastix","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Hardware","role_family":"Hardware","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":134000,"max_usd":244000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1301},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Apache TVM","optional":false},{"name":"Edge AI","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLIR","optional":false},{"name":"Quantization","optional":false},{"name":"SystemVerilog","optional":false},{"name":"Verilog","optional":false}],"status":"live","first_seen_at":"2026-02-19T03:29:49Z","employer_posted_date":"2026-02-19","last_verified_at":"2026-10-16T15:59:30Z","board_verified":true,"closed_at":null,"days_open":239,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":239},"description":"About Elastix AI\nWe are building the next-gen AI inference platform.\nDescription\nLocation: Seattle, WA (Hybrid - 3 days/week in office)\nAbout ElastixAI:\nElastixAI 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.\nRole Summary:\nWe 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.\nKey Responsibilities:\nContribute to the architectural definition, design, and implementation of a novel AI inference engine optimized for our specific ML workloads.\n\nCollaborate closely with ML engineers to understand and influence ML directions\n\nWork 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.\n\nPartner with cloud engineers to ensure the inference engine architecture aligns with target cloud hardware capabilities, deployment strategies, and performance/cost objectives.\n\nModel and analyze the performance, power, and area (PPA) trade-offs of different architectural choices.\n\nStay at the forefront of AI accelerator research, identifying emerging techniques and technologies relevant to our co-design approach.\n\nContribute to the RTL design, simulation, and verification efforts for the inference engine components.\n\nDrive the hardware roadmap for the inference engine, anticipating future AI model trends and optimization opportunities.\n\nFoster a culture of innovation and technical excellence within a highly interdisciplinary engineering team.\n\nRequired Qualifications:\nBS, MS or PhD in Computer Engineering, Electrical Engineering, or a related field.\n\nProven experience (5+ years) in hardware design, with a strong focus on designing/implementing hardware for AI/ML acceleration.\n\nDeep understanding of modern AI/ML models, particularly LLMs, and their computational characteristics.\n\nExperience with hardware implementation of ML optimization techniques (e.g., sparsity, quantization, pruning).\n\nProficiency in Verilog or SystemVerilog for RTL design and simulation.\n\nStrong understanding of memory system architecture, on-chip interconnects, parallel processing, and distributed computing.\n\nExcellent problem-solving skills and the ability to analyze complex systems.\n\nExceptional communication and interpersonal skills, with a demonstrated ability to work effectively in a highly interdisciplinary environment, collaborating with ML, software, and cloud/systems engineers.\n\nAbility to thrive in a fast-paced, dynamic startup environment with a strong bias for action/execution\n\nPreferred/Bonus Qualifications:\nKnowledge of compiler technologies for AI models (e.g., MLIR, TVM).\n\nFamiliarity with performance modeling and analysis tools.\n\nExperience with system-level integration and debugging.\n\nContributions to relevant research publications or open-source projects.\n\nUnderstanding of cloud computing environments and deploying hardware accelerators in the cloud.\n\nHigh-speed inter-chip networking experience\n\nWhat We Offer:\nA chance to be a foundational engineer in an innovative AI startup.\n\nA dynamic and collaborative work environment and the change to have a significant impact on new technology\n\nThe opportunity to work on challenging problems at the intersection of ML, software, and systems.\n\nCompetitive compensation and startup equity package\n\nComprehensive medical, dental, and vision coverage (100% paid by employer)\n\nFlexible Time Off (FTO)\n\nPaid parental leave\n\nCompany sponsored 401K Plan\n\nGym or fitness benefit\n\nCommuter benefit\n\nInvestment in employee learning & development","description_format":"text","description_chars":4504,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity","Flexible time off","Parental 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