AI Engineer

Job Description:
 

We are seeking a smart, self-driven AI Engineer with 2–5 years of experience who can work as an individual contributor in a fast-paced and results-oriented environment. The ideal candidate must be capable of working independently, taking ownership of AI and machine learning development tasks, and delivering high-quality intelligent solutions with minimal supervision. The role involves building, deploying, and optimizing AI/ML models, working with large datasets, and collaborating with engineering teams to integrate AI capabilities into real-world applications.

Key Skills & Experience:

• Designing and Developing AI models: This includes creating architectures, algorithms, and frameworks for generative AI.
• 2–5 years of hands-on experience in Artificial Intelligence, Machine Learning, or Data Science
• Strong programming skills in Python
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Strong understanding of machine learning algorithms, model training, and evaluation techniques
• Experience working with data analysis and processing tools such as Pandas, NumPy, and SQL
• Familiarity with Natural Language Processing (NLP), Computer Vision, or Generative AI technologies
• Experience building and integrating REST APIs or AI services into applications
• Knowledge of data preprocessing, feature engineering, and model optimization
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud is a plus
• Experience with Git and collaborative development workflows
• Strong analytical thinking, problem-solving skills, and ability to work independently

Roles & Responsibilities:
 

• Develop, train, and deploy machine learning and AI models for business applications
• Work with structured and unstructured data to build intelligent data-driven solutions
• Collaborate with software engineers, data teams, and product stakeholders to implement AI features
• Perform data preprocessing, feature engineering, and model tuning to improve performance
• Integrate AI models into applications, APIs, or enterprise systems
• Monitor and optimize model performance in production environments
• Document development processes, experiments, and model performance metrics
• Stay updated with the latest developments in AI, machine learning, and emerging technologies