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Lead AI Systems Engineer

2 months ago

Oxford, Oxfordshire, United Kingdom IC Resources Full time
Position Overview

Lead AI Systems Engineer

Location: Flexible (Hybrid options available)

IC Resources is on the lookout for a Lead AI Systems Engineer to become a vital part of our client's forward-thinking team. The ideal candidate will significantly contribute to enhancing AI model efficiency on advanced hardware architectures, focusing on optimizing models for specific hardware capabilities and facilitating training across diverse device environments. This role presents an exceptional chance to be involved in the evolution of pioneering AI acceleration technologies.

The successful candidate is expected to possess extensive engineering experience, particularly in the realm of large language models, with a strong emphasis on their inference and training across multiple devices, as well as hardware optimization, including GPUs, TPUs, and ASICs.

Key Responsibilities:

  • Performance Evaluation: Establish and uphold frameworks and methodologies for assessing AI models on specialized processors, ensuring peak performance.
  • Algorithm Development: Investigate and apply cutting-edge machine learning algorithms and methodologies to improve performance on AI hardware.
  • Collaboration with Engineering Teams: Partner closely with hardware engineers to comprehend processor architectures and refine AI models for these unique platforms.
  • Simulation Tool Creation: Design and implement simulation tools to evaluate AI performance on processors, aiding in system assessment and enhancement.
  • Integration with Development Processes: Work alongside cross-functional teams to incorporate benchmarking and simulation tools into the overall development workflow and product strategies.

Required Qualifications:

  • Educational Credentials: A degree in computer science, engineering, mathematics, or a related scientific discipline.
  • Familiarity with Computer Architectures: Knowledge of AI hardware platforms such as GPUs, TPUs, and ASICs.
  • Expertise in LLM Optimization: Experience in optimizing large language models for various hardware platforms.
  • Distributed Training Experience: Proficiency in training across multiple devices.
  • Performance Benchmarking: Background in evaluating and analyzing the performance of machine learning models.
  • Programming Proficiency: Strong skills in programming languages, particularly Python and C/C++.
  • Machine Learning Expertise: In-depth knowledge of machine learning techniques and frameworks, including TensorFlow and PyTorch.

Benefits:

  • Competitive Salary: £80-120k based on experience.
  • Flexible Working Arrangements: Hybrid working options available.
  • Generous Leave: 25 days of annual leave.
  • Equity Options: Stock options available.
  • Health Benefits: Comprehensive private health care scheme.
  • Visa Support: Assistance with skilled worker visa applications.

This position offers a unique opportunity to join an innovative team and play a crucial role in the advancement of transformative AI hardware technology.