{"id":99855,"url":"https://alion.io/job/normalcomputing-ai-engineer","title":"AI Engineer","company":{"id":39034,"name":"Normal Computing","domain":"normalcomputing.com","url":"https://alion.io/company/normalcomputing","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":100,"open_postings":4,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","London, United Kingdom","Copenhagen, Denmark"],"countries":["US","GB","DK"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":400000,"currency":"USD","period":"year","gross":null,"usd_annual":400000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Tool Use","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"RLAIF","optional":true},{"name":"RLHF","optional":true}],"status":"live","first_seen_at":"2026-07-15T20:47:57Z","employer_posted_date":"2026-07-15","last_verified_at":"2026-10-17T00:51:21Z","board_verified":true,"closed_at":null,"days_open":93,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":93},"description":"Normal Computing | Build with Us\nNormal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.\nThe Role\nAs an AI Engineer at Normal, you will build production systems that understand large technical documents, like chip design specifications, and turn them into code. You'll ship real improvements to customers weekly while pushing the boundaries of what's possible in AI for hardware through reinforcement learning, agentic coding, and exceptional software engineering.\nWhat You Will Own\nEnd-to-End Development: Lead AI development from initial concept through production deployment and iteration.\n\nDocument Understanding: Design and implement LLM-powered solutions that extract meaning from complex technical specifications.\n\nAgentic Systems: Handle multi-modal complexity and explore multi-agent and RL approaches for agentic code generation and tool use.\n\nProduction Quality: Design strategies to manage latency, output variance, and graceful error handling at scale.\n\nPlatform Integration: Collaborate with product and engineering teams to embed AI capabilities seamlessly into our platform.\n\nMentorship: Guide junior engineers and establish best practices for AI development.\n\nWhat Makes You a Great Fit\nPrevious experience delivering production AI systems involving language models, preferably involving document understanding and/or agentic workflows\n\nSolid software engineering skills with experience in distributed systems and production-grade code\n\nProficiency in Python and modern ML frameworks (PyTorch, Hugging Face, transformers)\n\nHands-on experience with prompt engineering, fine-tuning, and deploying large language models\n\nAbility to wrangle, clean, and preprocess large-scale, heterogeneous datasets\n\nAbility to explain complex AI concepts to both technical and non-technical stakeholders\n\nBonus Points\nExperience with hardware design, hardware verification, or EDA tooling\n\nExperience deploying AI systems in mission-critical or high-stakes production environments\n\nExperience with cloud platforms (AWS, GCP, Azure) for large-scale AI infrastructure\n\nResearch or applied experience with LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, or program synthesis\n\nOpen-source contributions or publications in AI/ML venues\n\nSkill in balancing cutting-edge innovation with production reliability and pragmatism\n\nEqual Employment Opportunity Statement\nNormal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.\nAccessibility Accommodations\nNormal Computing is committed to providing reasonable accommodations to individuals with disabilities. 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