AI Engineer

Key Responsibilities

• Design, develop, and deploy AI/ML models and algorithms for real-world applications.

• Work closely with data scientists and software engineers to integrate models into production environments.

• Research and implement appropriate ML algorithms and tools.

• Analyze large and complex data sets to derive actionable insights.

• Collaborate on system architecture, data pipelines, and model training frameworks.

• Continuously monitor, optimize, and improve model performance.

• Document processes, experiments, and outcomes for transparency and reproducibility.

• Stay updated with the latest research and trends in AI, ML, and deep learning.

Requirements

Must-Have Skills:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

• 2+ years of hands-on experience in AI/ML model development and deployment.

• Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.

• Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning).

• Experience with NLP, computer vision, or recommendation systems is a plus.

• Familiarity with data preprocessing, feature engineering, and model evaluation techniques.

• Experience with cloud platforms (AWS, GCP, Azure) for ML deployment.

• Strong problem-solving, analytical, and communication skills.

Good to Have:

• Experience with MLOps tools like MLflow, Kubeflow, or similar.

• Knowledge of big data tools (Spark, Hadoop) is a plus.

• Published research papers or contributions to open-source AI projects.