{"id":561437,"url":"https://alion.io/job/nvidia-senior-solutions-architect-large-scale-ai-training","title":"Senior Solutions Architect – Large Scale AI Training","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":774,"ghost_share":0.022,"stale_share":0.69,"repost_share":0.04,"time_to_fill_p50_days":38,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["France","United Kingdom","Spain","Poland","Switzerland"],"countries":["FR","GB","ES","PL","CH"],"hiring_countries":["FR"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":93000,"max_usd":184000,"period":"year","method":"role_seniority_country_cell","sample_n":13},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"HPC","optional":false},{"name":"Megatron-LM","optional":false},{"name":"Mixture of Experts","optional":false},{"name":"NVIDIA NeMo","optional":false},{"name":"Post-training","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLHF","optional":false},{"name":"Speculative Decoding","optional":false}],"status":"live","first_seen_at":"2026-09-08T00:00:00Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-10-30T23:07:35Z","board_verified":true,"closed_at":null,"days_open":53,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":53},"description":"We are looking for a senior Solutions Architect with strong knowledge of large-scale distributed training and Alignment of Neural Networks. The position involves supporting top EMEA AI Natives and research institutions in training/post training AI models, such as large Mixture-of-Experts (MoE) models. In this role, you will be the primary technical expert for AI organizations looking at some of the hardest infrastructure and algorithmic challenges in model training and alignment. You will bridge research and engineering, guiding customers on NVIDIA's full training stack (including Nemotron) while crafting NVIDIA product roadmap based on customers' feedback.\nWhat you'll be doing:\nBuild and manage strategic technical relationship with leading EMEA AI model builders developing large-scale foundation models. Collaborate closely with customers to define the software stack and infrastructure required for large-scale training and post-training workflows, including Reinforcement Learning (RL).\n\nServe as the go-to expert on distributed training strategies, guiding customers through efficient large-scale training and post training recipes using Deep Learning Frameworks such as PyTorch, Megatron-LM or NeMo (RL/Gym).\n\nHelp customers optimize training/finetuning efficiency at scale, covering GPU utilization, communication overlap, memory management at scale.\n\nCollaborate with NVIDIA's product and research teams to present customer needs.\n\nAnimate the developer community by building or supporting hackathons, demos, technical conferences.\n\nWhat we need to see:\nMS or PhD in Computer Science, Engineering, or equivalent experience.\n\nOver 7 years of practical experience in distributed AI training, including direct involvement with HPC and/or AI environments with multi-node GPU clusters.\n\nSolid understanding of training infrastructure and how it affects efficiency and scalability.\n\nStrong proficiency with Megatron-LM, NeMo, or equivalent distributed training frameworks.\n\nExcellent communication skills with an ability to engage both research scientists and infrastructure engineers.\n\nWays to stand out from the crowd:\nExperience in fine-tuning with Reinforcement Learning (RLVR, RLHF) at scale.\n\nExperience with LatentMoE, expert load balancing, and speculative decoding for MoE inference.\n\nPrior experience in an AI Datacenter/HPC center, national lab, or frontier AI lab environment.\n\nPublished work or open-source contributions in distributed training.\n\nWidely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer www.nvidiabenefits.com/\nNVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. 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