AI/ML engineer

Job Summary

As an AI/ML Engineer, you will design, implement, and deploy machine learning models and AI solutions, collaborating with cross-functional teams to solve real-world problems and drive business impact.

Job Roles & Responsibilities

• Design, develop, and implement machine learning and deep learning models.
• Preprocess, clean, and analyze large datasets for training and evaluation.
• Deploy ML models into production using frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Optimize model performance, scalability, and accuracy.
• Collaborate with data engineers, software developers, and product teams to integrate ML solutions.
• Stay updated with AI/ML research and industry best practices.
• Document models, experiments, and results clearly.
• Implement model monitoring, versioning, and continuous improvement processes

Cultural Expectations

• 4–7 years of experience in AI/ML or Data Science roles.
• Strong proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, Keras).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and ML deployment tools.
• Knowledge of NLP, computer vision, or recommendation systems is a plus.
• Strong problem-solving, analytical, and communication skills.
• Experience with SQL, NoSQL, and data pipelines is desirable.

Hiring Process

• Interview with hiring manager to assess technical skills.
• Live coding task to evaluate coding proficiency.
• Technical interview with senior member from the technical team.
• Final interview with Tech Lead/CTO.