Dimiour - LLM Engineer (3-6 yrs)

Job Description :

Key Responsibilities :

- Manage and enhance our internal LLM observability platform, ensuring it meets the evolving needs of the organization.

- Implement and maintain end-to-end MLOps/LLMOps pipelines, integrating seamlessly with the observability platform.

- Develop and optimize APIs, with a focus on FastAPI, to facilitate smooth interactions between data science and the observability platform.

- Collaborate with cross-functional teams to integrate observability features into the LLM lifecycle, enhancing model monitoring and debugging capabilities.

- Establish and maintain robust monitoring, logging, and alerting systems for LLM applications.

- Monitor LLM model performance and ensure high availability and scalability.

- Work closely with data scientists and engineers to troubleshoot issues, optimize performance, and enhance overall system reliability.

- Provide guidance and support to engineering teams on best practices for LLM deployment and maintenance.

- Experiment with new tools, frameworks, and techniques to enhance the efficiency and effectiveness of our LLM operations.

Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 3+ years of experience in machine learning, deep learning and natural language processing.

- Knowledge of NLP and experience with specific LLM frameworks (e. Hugging Face Transformers).

- Proficiency in MLOps/LLMOps tools and technologies, including but not limited to Kubernetes, Docker, and orchestration frameworks.

- Strong API development skills, particularly with FastAPI, and a solid understanding of RESTful principles.

- In-depth knowledge of the ML/LLM lifecycle, with a focus on observability and monitoring aspects.

- Expertise in version control systems (e., Git) and collaborative development workflows.

- Familiarity with cloud platforms (e., AWS, Azure, GCP) and experience deploying ML/LLM models in cloud environments.

- Excellent problem-solving and communication skills, with the ability to work effectively in a team environment.

Preferred Qualifications :

- Experience in designing, developing and training Large Language Models.

- Experience in fine-tuning pre-trained models to improve performance on specific tasks.

- Knowledge of reinforcement learning, transfer learning and other advanced ML techniques.

- Contribution to open-source NLP projects.

- Experience with automation and configuration management tools (e., Ansible, Terraform).

- Familiarity with container orchestration tools like Kubernetes.

- Knowledge of model monitoring and governance tools.