AI/ML Engineer - Python/Tensorflow

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Key Responsibilities

• Design, develop, and deploy robust ML models for classification, regression, recommendation, and anomaly detection tasks.
• Implement and optimize deep learning models using TensorFlow or related frameworks.
• Work with cross-functional teams to gather requirements, understand data pipelines, and deliver ML-powered features.
• Clean, preprocess, and explore large datasets to uncover patterns and extract insights.
• Evaluate model performance using standard metrics and implement strategies for model improvement.
• Automate model training and deployment pipelines using best practices in MLOps.
• Collaborate with data scientists, software developers, and product managers to bring AI features into production.
• Document model architecture, data workflows, and code in a clear and organized manner.
• Stay updated with the latest research and advancements in machine learning and AI.
  

Requirements

• Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field.
• 2-5 years of hands-on experience in developing and deploying ML models in real-world projects.
• Strong programming skills in Python and proficiency in ML libraries like TensorFlow, scikit-learn, NumPy, Pandas.
• Solid understanding of supervised, unsupervised, and deep learning algorithms.
• Experience with data wrangling, feature engineering, and model evaluation techniques.
• Familiarity with version control tools (Git) and deployment tools is a plus.
• Good communication and problem-solving skills.
  

Preferred (Nice To Have)

• Experience with cloud platforms (AWS, GCP, Azure) and ML services.
• Exposure to NLP, computer vision, or reinforcement learning.
• Familiarity with Docker, Kubernetes, or CI/CD pipelines for ML projects.