{"id":728935,"url":"https://alion.io/job/nace-research-engineer","title":"Research Engineer","company":{"id":678797,"name":"Nace.AI","domain":"nace.ai","url":"https://alion.io/company/nace-3","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"D","score":53,"open_postings":14,"ghost_share":0.786,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":166000,"max_usd":320000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-03-17T19:22:57Z","employer_posted_date":"2026-03-17","last_verified_at":"2026-11-04T23:48:02Z","board_verified":true,"closed_at":null,"days_open":232,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":231},"description":"About Us:\nAt Nace AI, we are redefining how professional services operate by delivering Sovereign Specialized Intelligence. As an applied research and product company, we equip enterprises with a comprehensive AI stack to build customized, secure intelligence tailored to their unique business needs.\nDriven by advanced Small Language Models and our dynamic metamodel framework, our flagship platforms - Nace Data Intelligence and the Nace SLM Cloud - enable true end-to-end business process automation. The result is transformative ROI: professional services firms using Nace AI are currently recovering 1,000 hours per client engagement, drastically reducing overhead and accelerating delivery.\nThe work we are doing has a meaningful impact across industries, and every hire at Nace AI plays a critical role in shaping the company’s trajectory. This is a unique opportunity to join a high conviction AI company at an early stage and directly influence its growth.\nIf building a world-class AI team from the ground up excites you, we’d love to talk.\nAbout the Role\nWe're looking for a Research Scientist to advance the core methods behind Nace AI's Small Language Models and metamodel framework. You'll work at the intersection of research and production, designing novel approaches to LLM adaptation, meta-learning, and hypernetworks, then carrying them from experimentation into systems that power Nace Data Intelligence and the Nace SLM Cloud.\nThis is a hands-on role on a small, high-caliber team. You'll own research problems end to end: framing the question, running rigorous experiments, publishing or open-sourcing where it makes sense, and partnering closely with engineering to ship what works. Your work will directly shape how enterprises build customized, secure intelligence on our stack.\nMinimum Qualifications\n3+ years of combined research and engineering experience in machine learning, including hands-on work with language models.Direct experience working with Large Language Models (LLMs) or Vision-Language Models (VLMs) in research or production settings\n\nStrong research background in Natural Language Processing, Machine Learning, or related disciplines with focus on language modeling\n\nProven track record in solving complex problems in language understanding, generation, or multimodal AI using rigorous quantitative methodologies\n\nDemonstrated ability to clearly communicate research findings to diverse technical audiences\n\nProficient programming skills in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow), with experience in distributed training and model optimization\n\nPreferred Qualifications\n5+ years of experience conducting applied ML research, with a sustained record of taking novel methods from experimentation to working systems.\n\nPhD in Computer Science, Computational Linguistics, or closely related field with focus on language models and adaptive learning systems\n\nProven research and engineering experience with LLMs/VLMs, particularly in meta-learning or parameter-efficient adaptation, as evidenced by grants, fellowships, patents, internships, or contributions to open-source projects\n\nFirst authored publications on language models, meta-learning, hypernetworks, or adaptive AI in recognized peer-reviewed conferences (ACL, EMNLP, NeurIPS, ICML, ICLR) or journals\n\nKaggle experience is a plus.\n\nPreferred Technical Experience\nResearch expertise in LLM reasoning, hypernetworks, multi-task learning, meta-learning, designing novel LLM adaptation methods, Online Continual 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