Machine Learning Engineer

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

Develop and deploy machine learning models ensuring scalability and efficiency in production environments Design and implement end-to-end machine learning pipelines from data ingestion and preprocessing to model evaluation and deployment Conduct rigorous experimentation and A B testing to optimize model performance and user experience Stay up-to-date with the latest advancements in machine learning and deep learning and apply them to solve real-world problems Automate model training evaluation and deployment processes to streamline workflows

Key Requirements:

• 3–7 years of experience building production-grade, scalable AI systems
• Strong expertise in supervised and unsupervised learning, deep learning, NLP, computer vision, and/or generative AI (LLMs)
• Experience training, fine-tuning, and deploying machine learning, neural network, and Agentic AI models
• Strong machine learning system architecture and design skills
• Experience building end-to-end production-grade ML pipelines covering data ingestion, model training, validation, deployment, and monitoring
• Knowledge of model serving and API development using frameworks such as FastAPI and Flask
• Familiarity with Docker, Kubernetes, CI/CD pipelines, MLflow, Kubeflow, and MLOps practices
• Experience deploying models on AWS and/or Azure
• Bachelor's degree in Computer Science, Engineering, or a related field (Master's or PhD preferred)