About the Job:
We’re Hiring: MLOps / LLMOps Engineer. As part of a cross-functional team of engineers, data scientists, and product owners, you’ll design, implement, and scale MLOps & LLMOps infrastructure to take machine learning models from development to production—seamlessly and efficiently. If you’re passionate about production-grade ML systems and cutting-edge LLM workflows, the company is the place for you.
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Requirements:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- 3+ years of experience in MLOps / ML Engineering / Platform Engineering
- Hands-on experience with Docker, Kubernetes, EKS
- Good-to-have experience with LLMOps best practices (monitoring, drift detection, prompt management, feedback loops)
- Familiarity with model optimization techniques (quantization, distillation, pruning)
- Strong experience in monitoring, observability, and alerting for ML systems
Technical Skills:
- Cloud: AWS
- Orchestration: Kubernetes, EKS
- Programming: Python
- ML Frameworks: PyTorch / TensorFlow
- Distributed Systems: Slurm, Ray
- Hardware: Nvidia DGX
- MLOps Tools: Kubeflow, MLflow
- LLM Stack: LangChain, Chainlit, LlamaIndex
Key Responsibilities:
- Build and manage containerized ML & LLM deployments using Docker & Kubernetes
- Implement LLMOps practices for monitoring, drift detection, and continuous improvement
- Optimize models for efficient inference on AWS
- Design monitoring & observability systems for performance, latency, and resource usage
- Lead prompt engineering and prompt management strategies
- Collaborate with data scientists and engineers for seamless ML integration
- Automate model versioning and deployment across environments
- Design and maintain CI/CD pipelines for ML workflows
- Ensure scalable, reliable, and efficient MLOps environments
- Maintain strong documentation and operational standards
- Stay up to date with emerging trends in MLOps & LLMOps
Soft Skills:
- Strong problem-solving ability
- Excellent communication and collaboration skills
- Self-driven and proactive mindset
Work Conditions:
On-site, Full-time
Location:
Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates
