Machine Learning Engineer

Dicetek LLC; Abu Dhabi; On-site; AED 300,000 - 550,000; Full time

Job summary

Dicetek LLC leads the design and development of scalable machine learning models and AI-driven solutions to tackle complex business challenges. You will work on large datasets, train and deploy production-grade models, and build end-to-end ML pipelines from data ingestion to deployment.

The role requires expertise in supervised/unsupervised learning, deep learning, NLP, CV, or generative AI, plus strong ML system architecture skills.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• Master or PhD in Computer Science or a related field preferred.
• 3-7 years of experience in building production-grade, scalable AI systems.
• Experience with deployment and ML system architecture.

Responsibilities

• Work with large and complex data sets to solve challenging business problems.
• Efficient training and deployment of standard ML NN and Agentic models.
• Develop, train and optimize ML models using state-of-the-art algorithms and frameworks.
• Build production-grade end-to-end ML pipelines from data ingestion to deployment.
• Automate workflows for model training, testing and deployment using CI/CD and MLOps tools.
• Collaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutions.
• Fine-tune SLMs/LLMs and build complex AI architectures (3-7 years) of experience in production-grade systems.
• Expert in supervised/unsupervised learning, DL, NLP, CV, or generative AI (e.g., LLMs).
• Strong ML system architecture skills.
• Understanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.
• Knowledge of Docker, Kubernetes, CI/CD pipelines and MLOps tools (MLflow/Kubeflow).
• Experience deploying models on AWS or Azure.

Skills

Machine Learning

AI-driven solutions

ML system architecture

Education

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

Master or PhD in Computer Science or a related field

Tools

Docker

Kubernetes

CI/CD pipelines

MLflow

Kubeflow

AWS

Azure

FastAPI

Flask

Job description

Designs and develops scalable machine learning models and AI-driven solutions to address complex business challenges and enhance decision-making processes

KEY RESPONSIBILITIES

• Work with large and complex data sets to solve challenging business problems


• Efficient training and deployment of standard ML NN and Agentic models


• Develop train and optimize machine learning models using state-of-the-art algorithms and frameworks


• Build production grade end-to-end ML pipelines including data ingestion transformation model training validation and deployment


• Automate workflows for model training testing and deployment using CI CD pipelines and MLOps tools


• Collaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutions


• Finetune SLMs LLMs and build complex AI architectures (3-7) years of experience in building production grade, scalable AI systems


• Expert in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs).


• Strong ML system architecture skills


• Understanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference


• General Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps)


• Comfortable with deploying models on AWS or Azure

Minimum Educational qualifications

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

Preferred Education qualifications

• Master or PhD in Computer Science or a related field

Skills

• Machine Learning


• AI-driven solutions


• ML system architecture