Senior ML Engineer - End-to-End Production AI

Finesse FZ LLC; Abu Dhabi; On-site; AED 120,000 - 190,000; Full time

Job summary

Finesse FZ LLC in Abu Dhabi invites an experienced Senior ML Engineer to develop and deploy scalable AI models in production. You will design end-to-end ML pipelines spanning data ingestion, training, validation, deployment, and monitoring, with a focus on efficiency and reliability.

You will experiment with supervised/unsupervised learning, DL, NLP, computer vision, and generative AI, and contribute to robust ML system architecture.

Qualifications

• Bachelor's degree in CS, Engineering, or related field.
• Experience with production-grade ML systems is required.
• Strong knowledge of ML/DL, NLP, CV, and/or generative AI.
• Experience building end-to-end ML pipelines and deployment workflows.

Responsibilities

• Develop and deploy scalable ML models in production.
• Design end-to-end ML pipelines from data ingestion to deployment.
• Conduct rigorous experiments and A/B tests to optimize performance.
• Stay up-to-date with ML/DL advancements and apply them to problems.
• Automate model training, evaluation, and deployment workflows.

Skills

Production-grade AI systems

Supervised learning

Unsupervised learning

Deep learning

NLP

Computer vision

Generative AI (LLMs)

Model deployment

ML pipelines

Data ingestion

API development

FastAPI

Flask

Docker

Kubernetes

CI/CD

MLflow

Kubeflow

MLOps

AWS

Azure

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

FastAPI

Flask

Docker

Kubernetes

MLflow

Kubeflow

CI/CD pipelines

Job description

Finesse FZ LLC in Abu Dhabi invites an experienced Senior ML Engineer to develop and deploy scalable AI models in production. You will design end-to-end ML pipelines spanning data ingestion, training, validation, deployment, and monitoring, with a focus on efficiency and reliability.

You will experiment with supervised/unsupervised learning, DL, NLP, computer vision, and generative AI, and contribute to robust ML system architecture.