AI / ML Engineer

About This Role

General Description

Join a fast-growing, technology-driven organization delivering advanced AI platforms and intelligent digital solutions across the life insurance and digital health sectors.

We are looking for an AI / ML Engineer with strong hands-on experience in MLOps and LLM-based systems to support the development, evaluation, and monitoring of production-grade AI solutions.

This role is ideal for a highly technical engineer who can build, review, and optimize AI pipelines while ensuring model performance, reliability, and scalability across real-world deployments.

You will work closely with AI leads, architects, and engineering teams to support AI lifecycle management, from experimentation to deployment and continuous improvement.

This is a freelance / contract, onsite role based in Dubai , with an urgent hiring timeline, supporting high-impact AI initiatives in regulated environments.

Key Responsibilities

• Design, build, and maintain AI/ML pipelines for LLMs, RAG systems, and multi-modal models.
• Review and optimize model pipelines, ensuring performance, scalability, and reliability.
• Implement MLOps practices including model versioning, deployment, monitoring, and rollback strategies.
• Develop and maintain evaluation frameworks for AI models (accuracy, latency, bias, cost, performance).
• Monitor production AI systems and identify opportunities for optimization and improvement.
• Support testing and validation of voice, text, and vision models.
• Implement and support AI observability tools for tracking system performance and behavior.
• Collaborate with cross-functional teams to ensure production readiness and deployment success.
• Contribute to continuous improvement of AI systems through feedback loops and evaluation strategies.

Required Skills & Experience

• 3–5+ years of experience in AI/ML engineering, MLOps, or LLM-based systems.
• Strong hands-on experience with Python and AI frameworks.
• Experience working with LLMs, RAG pipelines, and AI model evaluation .
• Strong understanding of MLOps practices (deployment, monitoring, versioning, rollback).
• Experience reviewing and optimizing AI pipelines.
• Familiarity with voice and text models .
• Experience with performance monitoring and model evaluation frameworks.
• Strong problem-solving and analytical skills.
• Ability to work independently in a fast-paced contract environment.

Preferred / Nice to Have

• Experience with RLHF (Reinforcement Learning from Human Feedback).
• Familiarity with vision-language models (VLMs).
• Experience with AI observability tools (e.g., Langfuse, LangSmith).
• Experience in regulated industries (banking, insurance, healthcare, government).
• Experience working with distributed or enterprise-scale systems.