Artificial Intelligence / Machine Learning Engineer

We are seeking an experienced Artificial Intelligence / Machine Learning Engineer to support the design, development, and implementation of advanced AI-driven solutions. This role requires strong hands-on experience building and deploying machine learning models, applying AI technologies to real-world problems, and collaborating with cross-functional teams to deliver scalable solutions.

The ideal candidate will have a strong technical background in AI development, machine learning, and data-driven application design, with the ability to quickly assess business needs and translate them into practical AI solutions.

Key Responsibilities

• Develop proof-of-concepts (POCs) and production-ready AI applications.
• Design, develop, and deploy AI and machine learning models to solve complex business problems.
• Build and optimize predictive models, NLP models, and data-driven algorithms.
• Collaborate with engineering, product, and data teams to integrate AI solutions into existing platforms and applications.
• Evaluate datasets, perform feature engineering, and prepare data for model training and testing.
• Monitor model performance and continuously improve accuracy and scalability.
• Document models, architecture, and implementation approaches for maintainability and scalability.
• Provide technical guidance on AI strategy, architecture, and best practices.

Required Qualifications

• Strong, demonstrable experience in Artificial Intelligence development and implementation.
• Proven machine learning experience with practical, real-world application.
• Experience building, training, and deploying machine learning models in production environments.
• Strong programming skills in Python, R, or similar languages.
• Experience with ML frameworks
• Experience working with large datasets and data pipelines.
• Knowledge of model evaluation, optimization, and performance tuning.
• Strong analytical and problem-solving skills.

Preferred Qualifications

• Experience with Natural Language Processing (NLP), Generative AI, or deep learning models.
• Experience integrating AI with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with MLOps practices, model deployment pipelines, and containerization tools (Docker, Kubernetes).
• Experience building AI-powered applications, automation tools, or intelligent workflows.