Machine Learning Backend Engineer

Description

For our client, a global IT Consultancy delivering first-class technology solutions, we are looking for a Machine Learning Backend Engineer to join them in Al-Khobar, Saudi Arabia.

You will play a crucial role in developing and maintaining the back-end components of their web applications using the MERN (MongoDB, ExpressJS, ReactJS, Node.js) stack. You will contribute to machine learning initiatives, manage AI solutions deployments, and employ various machine learning techniques.

Responsibilities:

• Develop and maintain scalable back-end components of web applications using the MERN stack.
• Utilize your advanced experience in programming languages such as JavaScript (Node.js) or Python.
• Apply your knowledge of databases (e.g., MongoDB, MySQL, Oracle, SQL Server) and caching mechanisms (e.g., Varnish, Memcached, Redis).
• Employ Docker and Kubernetes for application deployment and management.
• Collaborate with cross-functional teams to design and implement efficient server-side architecture.
• Play a key role in managing AI solutions deployments and ensuring their successful integration and operation.
• Demonstrate expertise in machine learning techniques such as clustering, decision tree learning, artificial neural networks, etc.
• Fine-tune and optimize machine learning models for performance and accuracy.
• Collaborate with data scientists to design and implement machine learning algorithms.
• Integrate machine learning capabilities into existing products and ensure their seamless operation.

Professional background

• +6 years of professional experience
• Strong programming skills in languages such as JavaScript (Node.js) or Python.
  
• Experience with the MERN stack: MongoDB, ExpressJS, ReactJS, Node.js.
  
• Knowledge of databases and caching mechanisms, such as MongoDB, MySQL, Oracle, SQL Server, Varnish, Memcached, and Redis.
  
• Familiarity with Docker and Kubernetes for containerization and orchestration.
  
• Experience in managing AI solutions deployments and integrating machine learning capabilities.
  
• In-depth understanding of machine learning techniques like clustering, decision tree learning, artificial neural networks, etc.
  
• Strong analytical, problem-solving, and communication skills.