We are seeking a highly skilled and motivated Machine Learning Operations Engineer (MLOps) with a specialization in Large Language Models (LLMs) to join our dynamic team at Gini-Apps. In this role, you will play a pivotal role in designing, implementing, and optimizing the infrastructure that supports the research, training, fine-tuning, and evaluation of LLMs.

Responsibilities:

• Collaborate with data scientists to design, implement, and optimize infrastructure supporting Large Language Model (LLM) research, training, fine-tuning, and evaluation.
• Work closely with research teams to enhance the efficiency and scalability of LLM-related processes.
• Stay current with industry trends and emerging technologies in machine learning operations.
• Contribute to the continuous improvement of pipeline and workflow practices.
  
  

Requirements:

• Bachelor's or advanced degree in Computer Science, Engineering, or a related field.
• Expertise in designing and optimizing machine-learning operations, with a preference for LLMOps.
• Proficiency in programming languages such as Python, PowerShell, Bash.
• Strong understanding of containerization and orchestration tools (e.g., Docker).
• Experience with version control systems (e.g., Git).
• Knowledge of cloud platforms (Azure, AWS, or GCP), with a preference for Azure and Azure Machine Learning.
• Solid understanding of networking, security, and infrastructure concepts.
• Excellent problem-solving and troubleshooting skills.
• Preference for familiarity with Large Language Models and Natural Language Processing (NLP), and experience with researching, training, and fine-tuning LLMs.
• Advantage: Experience with CI/CD tools such as Jenkins, GitLab CI, and CircleCI. Implement and maintain automated testing and deployment processes for machine learning models. Monitor and troubleshoot production machine learning systems to ensure high availability and performance.