Senior LLM Engineer
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Job Description
Job Description: Senior LLM Engineer (Arabic Fluency Required)
Location: Riyadh, Saudi Arabia
Job Type: Full-time
Key Responsibilities
Location: Riyadh, Saudi Arabia
Job Type: Full-time
Key Responsibilities
- Develop and deploy end-to-end AI/ML solutions using Python and LLM/GenAI frameworks and tools
- Design, implement, and maintain CI/CD pipelines, containerize LLM models, and deploy them on cloud or on-premise environments
- Conduct thorough testing, deployment, and ongoing maintenance of models to ensure optimal performance throughout their lifecycle
- Research, design, and train innovative applications leveraging LLMs to solve complex real-world problems
- Build prototypes and proofs-of-concept (PoCs) to demonstrate solution feasibility and value, and provide robust architecture solutions
- Design and implement Retrieval-Augmented Generation (RAG) pipelines for specific use cases
- Develop and optimize LLM embeddings for diverse applications, including custom training pipelines
- Provide technical guidance to clients adopting LLM technologies, ensuring seamless integration and effective use
- Collaborate with teams to ensure compliance with Responsible AI standards and protocols
- Education: Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or related fields (final-year students may be considered)
- Experience:
- 3+ years of hands-on experience in AI/ML technologies and software engineering
- 2+ years of experience in shell scripting and NLP, including at least 1+ year of experience working with LLM/GenAI technologies like OpenAI API, ChatGPT, GPT-4, LangChain, HuggingFace Transformers, or similar
- 1+ year of experience with prompt engineering and vector databases (e.g., pgvector)
- 2+ years of experience with AWS, GCP, or Microsoft Azure
- 2+ years of experience with MLOps, CI/CD pipeline development, containerization, and deploying models in production
- Strong proficiency in Python, including experience with AI and ML libraries such as PyTorch and TensorFlow
- Proven experience fine-tuning and deploying LLMs, as well as implementing RAG architectures
- Excellent problem-solving skills, with the ability to optimize model performance
- Fluency in both Arabic and English, with the ability to communicate complex technical concepts to non-technical stakeholders
- In-depth expertise in a specific domain or industry, particularly in NLP/LLM applications
- Applied research experience in developing production-grade LLM solutions
- Knowledge of Responsible AI standards and their implementation
- Familiarity with MLflow or other experiment-tracking tools
- Experience with cloud platforms such as GCP for AI/ML workloads
- Proficiency in Python programming and AI/ML frameworks
- Hands-on experience in fine-tuning, deploying, and maintaining LLMs
- Solid understanding of RAG pipelines, embeddings, and vector databases
- Expertise in MLOps and best practices for model deployment
- Automated testing experience to ensure robust pipelines
More Info
Key Skills
LangChain
Prompt engineering
Vector databases
LLM GenAI frameworks and tools
OpenAI API
ChatGPT
HuggingFace Transformers
GPT-4
RAG architectures
