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Member of Technical Staff - Frontier AI (Remote)

  • Canada
  • Remote
  • Posted Aug 14, 2026
  • 1 position

US$600,000–US$2,000,000 / year

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Employment type
Full-time
Experience level
Lead · 10+ years
Minimum education
Master’s degree
Posting language
English
Working hours
40 hours per week
Seniority
Associate

Job summary

The role involves designing and optimizing next-generation AI architectures and leading research to improve model efficiency and scalability. The candidate will collaborate with cross-functional teams to integrate AI solutions into production and publish technical findings.

Job details

Role: Member of Technical Staff - Frontier AI (Remote) Location: Remote (Work from Anywhere) Job Type: Full-Time Payout: $600K - $2000K/yr Role Overview: We are hiring for one of our clients, seeking a Member of Technical Staff (Frontier AI) to work on a full-time basis. This role focuses on advancing cutting-edge AI models and systems at the frontier of the field. The position involves deep technical contributions to research and development efforts that push the boundaries of current AI capabilities. Key Responsibilities: • Design, implement, and optimize next-generation AI architectures and algorithms. • Lead research initiatives to improve model efficiency, scalability, and performance. • Collaborate with cross-functional teams to integrate AI solutions into production systems. • Publish findings and contribute to technical reports, whitepapers, or conference submissions. • Evaluate and benchmark new AI models, frameworks, and hardware accelerators. Required Skills & Qualifications: • PhD in Computer Science, AI, Machine Learning, or a related field, or equivalent industry experience. • Proficiency in deep learning frameworks such as PyTorch or TensorFlow. • Strong background in large-scale distributed training and model optimization techniques. • Experience with AI hardware and accelerator architectures (e.g., GPUs, TPUs). • Demonstrated ability to conduct independent research and drive technical projects. • Familiarity with reinforcement learning, generative models, or multi-modal AI systems. • Excellent debugging and analytical skills for complex AI systems. • Ability to communicate technical concepts effectively to diverse audiences. More About the Opportunity: This role offers a unique opportunity to work with a global leader in the Software Development | Technology, Information and Internet industry, contributing to the development of state-of-the-art AI systems that will shape the future of the field. The position includes access to advanced computational resources and collaboration with leading researchers and engineers in the AI community. Equal Opportunity Employer: We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications. Apply Now!

What you’ll do

The role involves designing and optimizing next-generation AI architectures and leading research to improve model efficiency and scalability. The candidate will collaborate with cross-functional teams to integrate AI solutions into production and publish technical findings.

Requirements

Requires a PhD in Computer Science, AI, or Machine Learning, or equivalent industry experience, with proficiency in PyTorch or TensorFlow. Candidates must have a strong background in large-scale distributed training and experience with AI hardware accelerators.

Listed skills

  • Production · Preferred
  • Analytical · Preferred
  • Technical · Preferred
  • Training · Preferred
  • Collaboration · Preferred
  • staff · Preferred
  • Teams · Preferred
  • Machine learning · Preferred
  • Development · Preferred
  • Time · Preferred
  • future · Preferred
  • efficiency · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • PyTorch
  • TensorFlow
  • Distributed Training
  • Model Optimization
  • AI Hardware Architectures
  • GPUs
  • TPUs
  • Reinforcement Learning
  • Generative Models
  • Multi-modal AI Systems
  • Deep Learning
  • AI Architecture Design

Job areas

  • Technology
  • Science & Research
  • Software
  • Engineering
  • Data & Analytics

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