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Machine Learning Engineer (LLM Fine-Tuning) - Remote

Posted Yesterday
Software Development
Contract
Worldwide
Up to 78 USD/hour

Overview

The Machine Learning Engineer will focus on fine-tuning and deploying Large Language Models (LLMs) to enhance user interactions with expert insights.

In Short

  • Fully remote role.
  • Contract position with a rate of up to USD78/hour.
  • Design, fine-tune, and deploy LLMs.
  • Optimize ML models for performance, cost, and latency.
  • Build and maintain data pipelines for model training.
  • Collaborate with teams to integrate AI features.
  • Explore new techniques in prompt engineering and model optimization.
  • Strong background in machine learning engineering required.
  • Experience with Python and ML frameworks needed.
  • Excellent communication skills are essential.

Requirements

  • Proven experience with LLMs (OpenAI, Anthropic, etc.).
  • Strong background in machine learning engineering.
  • Experience with Python and frameworks like PyTorch and TensorFlow.
  • Understanding of NLP and model evaluation.
  • Experience building end-to-end ML systems.
  • Familiarity with MLOps tools and cloud infrastructure.
  • Excellent communication and documentation skills.

Benefits

  • Work with a high-impact team passionate about AI.
  • Fully remote and flexible working schedule.
  • Opportunity to influence the AI roadmap of the company.
G2i logo

G2i

G2i Inc. is a forward-thinking company specializing in the development of advanced AI models, particularly in the realm of generative AI. They focus on creating high-quality training data through a collaborative and remote work environment, allowing software engineers to engage with cutting-edge technology. With a commitment to flexibility and a diverse range of projects, G2i Inc. offers opportunities for engineers to contribute to significant advancements in AI while enjoying the benefits of a remote work lifestyle. The company values expertise in Python and encourages continuous learning and engagement within the coding community.

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