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Designworks Talent LLC
Designworks Talent LLC
B2BPersonāla atlasePersonāla tehnoloģijas
Designworks Talent LLC ir personāla atlases un talantu konsultāciju uzņēmums, kas apkalpo strauji augošus jaunuzņēmumus un globālus lieluzņēmumus. Uzņēmums, kas dibināts 2009. gadā, apvieno pieredzējušus personāla atlases speciālistus ar mākslīgā intelekta atbalstītiem rīkiem, lai veicinātu ātrāku un mērķtiecīgāku darbinieku atlasi. Tā darbība ietver pilna servisa kandidātu meklēšanu, uz projektiem balstītu personāla atlasi un elastīgus pēc pieprasījuma pielāgojamus modeļus, kā arī mērogojamu darbā pieņemšanas stratēģiju, personāla atlases operācijas, uzņēmuma līmeņa talantu piesaistes vadību, uz datiem balstītu kandidātu meklēšanu un kandidātu pieredzi. Komandas pieeja ir izstrādāta, lai organizācijām nodrošinātu pielāgojamu atbalstu, mainoties to personāla atlases vajadzībām.
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Vakances uzņēmumā

Staff AI Training Infrastructure Engineer

Lead the development of distributed GPU training infrastructure for large AI models. Improve reliability, efficiency, fault tolerance, and production training operations at scale.

USAmerikas Savienotās ValstisWAVašingtonaHibrīdiPilna slodzeVadošais speciālistsNepieciešamā Valoda: angļuInfrastruktūras inženieris
KubernetesMākonisNode.jsPyTorchRaySadalītās sistēmas

Apraksts

  • Build and scale distributed training infrastructure for large AI models across extensive GPU clusters
  • Design systems that improve training reliability, efficiency, and resource utilization
  • Develop fault-tolerant solutions for checkpointing, recovery, and large-scale training operations
  • Integrate AI models into production training pipelines alongside platform, orchestration, and performance engineering teams
  • Investigate and resolve issues affecting training throughput, stability, reliability, and cost efficiency
  • Create tools and automation that enhance the experience of AI researchers and engineers
  • Define best practices for training infrastructure, operations, and platform reliability
  • Help shape the AI infrastructure platform as an early member of the engineering team

Prasības

  • Practical experience building and operating distributed training systems or large-scale machine learning infrastructure
  • Experience supporting large AI models, foundation models, post-training workflows, or comparable machine learning systems
  • Strong understanding of reliability, scalability, and efficiency challenges in multi-node GPU training
  • Experience connecting training systems to production machine learning pipelines
  • Advanced programming ability and experience working with complex distributed systems
  • Demonstrated ability to independently lead technically demanding projects
  • Experience with distributed training frameworks such as PyTorch Distributed, DeepSpeed, Megatron-LM, Ray, or comparable technologies
  • Experience with supervised fine-tuning, reinforcement learning from human feedback, or other post-training methods
  • Experience operating AI training infrastructure at scale for a hyperscaler, AI research organization, cloud provider, or GPU cloud
  • Background optimizing GPU utilization, training performance, or distributed system reliability
  • Familiarity with Kubernetes, containerized AI workloads, and large-scale infrastructure platforms
  • U.S. work authorization is required
  • Visa sponsorship is not currently available

Priekšrocības

  • Some roles offer merit increases, annual bonuses, and long-term incentives based on individual performance
  • Medical, dental, and vision insurance for U.S.-based employees
  • 401(k) plan with company matching
  • Paid holidays each calendar year
  • Hybrid work arrangement

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