Senior Machine Learning Engineer (NLP/LLMs)

About the Role

Key Responsibilities

• Design, develop, and deploy NLP and LLM-based solutions for real-world applications.
• Translate research papers and experimental models into production-ready systems.
• Architect scalable machine learning pipelines for performance and reliability.
• Integrate machine learning models into company platforms with product and engineering teams.
• Run experiments, evaluate models, and optimize accuracy, efficiency, and cost.
• Track advances in NLP, LLMs, and generative AI.
• Guide junior engineers and help build a high-performance AI team.

Education and Experience

• An MSc or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field is required.
• The role requires at least 5 years of professional experience in ML or NLP, including at least 3 years working with LLMs.

Core Expertise

• Strong NLP knowledge covering transformers, embeddings, and sequence models is required.
• Hands-on LLM experience should include fine-tuning, prompt engineering, and model evaluation.
• Experience with LangChain or Haystack is preferred for building LLM-powered applications.
• The role requires understanding of ML system design and production deployment.

Software Engineering Skills

• Proficiency in Python and ML frameworks including PyTorch, TensorFlow, and Hugging Face is required.
• Strong knowledge of software engineering principles, version control, testing, and CI/CD is required.
• Experience with distributed systems, APIs, and microservices is required.
• Familiarity with AWS, GCP, or Azure and containerization with Docker or Kubernetes is preferred.

Working Style

• Excellent analytical skills and the ability to work independently in a fast-paced startup environment are required.
• Experience in Arabic NLP or multilingual LLMs is a strong plus.

Joining Hudhud