AI Engineer, LLMs

Logical Intelligence

$130K — $180K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Deep understanding of transformer models and capability to modify architecture significantly.
  • Expertise in Python/C++, specifically for high-performance computing and machine learning tools.
  • Proficient with Deep Learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Experience in optimizing machine learning systems, especially for large language models.
  • Knowledge of current state-of-the-art LLM reasoning techniques and approaches.
  • Minimum of 3 years' experience in ML infrastructure and DataOps, including distributed training.
  • Strong collaborative and communication skills.

Responsibilities

  • Implement new reasoning algorithms and models.
  • Evaluate various reasoning approaches including latent space reasoning.
  • Pre-train, fine-tune, and enhance state-of-the-art large language models.
  • Optimize and scale LLM pipelines for performance.
  • Modify frameworks to speed up machine learning development.
  • Integrate practical solutions with cross-team results for optimal outcomes.

Benefits

  • Opportunity to work at the forefront of AI technology.
  • Collaboration with a skilled team of AI experts and engineers.
  • Exposure to cutting-edge technologies in machine learning infrastructure.
  • Possibility to influence advancements in logical reasoning and AI capabilities.
Full Job Description
About the role

Join our team as an AI Engineer and help us push the boundaries of what's possible in logical reasoning! We're looking for a motivated individual to design, implement, and refine efficient Large Language Models (LLMs) pipelines for scaled distributed training. You'll be at the forefront of designing and refining algorithms that go beyond the capabilities of traditional LLMs. You'll work closely with a talented team of AI experts, EBM specialists, formal verification engineers, and software developers to create groundbreaking solutions.
What you'll do
  • Implement new reasoning algorithms and models
  • Evaluate reasoning approaches, including latent space reasoning
  • Pre-train, fine-tune, and modify the State-of-the-Art LLMs
  • Optimizing and scaling LLM pipelines
  • Adjust frameworks and interfaces to accelerate machine learning development
  • Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution
Qualifications
  • Deep understanding of transformers' internals, and ability to make radical changes to the architecture and handle higher-order derivatives
  • Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like PyTorch /TensorFlow/JAX
  • Expertise in optimizing machine learning systems, including general techniques and LLM-specific optimizations
  • Understanding state-of-the-art approaches in LLM reasoning
  • Ability to understand complex learning approaches, such as energy-based models
  • 3+ years of production experience in ML Infra, DataOps, distributed training. Proficiency with Kubernetes clusters and distributed compute assets
  • Strong communication and teamwork skills
  • Readiness to explore and promote cutting edge technologies in ML Infrastructure domain and beyond


Bonus Points:
  • Demonstrated publications in any of the major conferences
  • Experience in EBM or latent reasoning
  • Demonstrated publications in any of the major conferences
  • Mathematical Reasoning - discrete math and logic


logicalintelligence.com

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