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Designworks Talent LLC
Designworks Talent LLC
B2BHR TechRecruitment
Designworks Talent LLC is a recruitment and talent advisory firm serving high-growth startups and global enterprises. Founded in 2009, the company combines experienced recruiters with AI-enabled tools to support faster, more targeted hiring. Its work spans full-service searches, project-based recruiting, and flexible on-demand models, alongside scalable hiring strategy, recruiting operations, enterprise talent acquisition leadership, data-informed sourcing, and candidate experience. The team’s approach is designed to give organizations adaptable support as their hiring needs evolve.
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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.

USUnited StatesWAWashingtonHybridFull-timeLeadEnglish RequiredInfrastructure Engineer
CloudDistributed SystemsKubernetesNode.jsPyTorchRay

Description

  • 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

Requirements

  • 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

Benefits

  • 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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