{"id":750724,"url":"https://alion.io/job/sciforium-pre-training-research-engineer","title":"Pre-training Research Engineer","company":{"id":716759,"name":"Sciforium","domain":"sciforium.ai","url":"https://alion.io/company/sciforium-2","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":85,"open_postings":5,"ghost_share":0,"stale_share":0.8,"repost_share":0,"time_to_fill_p50_days":11,"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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":165000,"max":225000,"currency":"USD","period":"year","gross":null,"usd_annual":225000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Pre-training","optional":false},{"name":"Flax","optional":true},{"name":"FSDP","optional":true},{"name":"JAX","optional":true},{"name":"Megatron-LM","optional":true},{"name":"XLA","optional":true}],"status":"live","first_seen_at":"2026-08-31T18:42:30Z","employer_posted_date":"2026-08-31","last_verified_at":"2026-11-04T11:40:28Z","board_verified":true,"closed_at":null,"days_open":64,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":64},"description":"Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. Backed by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications.\nAbout the role\nAs a Pre-training Research Engineer, you’ll focus on model implementation, pertaining and scaling, and improving the quality of our byte-native and multimodal foundation models. You’ll build and iterate quickly on research ideas, contribute production-grade training code and infrastructure, and help deliver high-quality base models that can serve real-world use cases at scale.\nKey Responsibilities\nPre-training & Scaling\nTrain large byte-native and multimodal foundation models across massive, heterogeneous corpora.\n\nImplement and evaluate new model architectures, training objectives, and optimization methods.\n\nDevelop stable pre-training recipes and run scaling experiments for novel architectures.\n\nConduct ablations and analyze training dynamics, model behavior, and base-model quality.\n\nWork with data and distributed training engineers to improve training efficiency, reliability, and scalability.\n\nMust-Haves\n5+ years of experience in machine learning research or engineering, with a proven track record of developing and pre-training large language or multimodal foundation models.\n\nSoftware Engineering: Strong general software engineering skills, with the ability to write robust and performant training code.\n\nML Foundations: Solid understanding of deep learning fundamentals and modern pre-training methods and literature.\n\nResearch and Experimentation: Ability to quickly implement research ideas and evaluate them using clear baselines, ablations, metrics, and analysis.\n\nGPU and Distributed Training: Hands-on experience running training workloads in GPU-based environments, with familiarity with distributed training.\n\nEducation: MS in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field.\n\nNice-to-Haves\nPhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field.\n\nJAX Ecosystem: Extensive experience with the JAX, Flax, and XLA stack.\n\nLarge-Scale Distributed Training: Experience with multi-node pre-training using systems such as FSDP, ZeRO, or Megatron.\n\nTraining Recipes and Scaling: Experience developing training recipes, ablations, or scaling experiments.\n\nMonitoring and Reproducibility: Experience owning end-to-end training and evaluation pipelines with monitoring and reproducibility.\n\nEducation\nMS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related field.\n\nBenefits include\nMedical, dental, and vision insurance\n\n401k plan\n\nDaily lunch, snacks, and beverages\n\nFlexible time off\n\nCompetitive salary and equity\n\nEqual opportunity\nSciforium is an equal opportunity employer. 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