Python / AI-ML Developer

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Job Summary:

We are looking for a passionate and skilled Python / AI-ML Developer with 2–5 years of experience to join our data science and engineering team. The ideal candidate will be responsible for building intelligent solutions, designing machine learning models, and developing scalable Python-based systems. This role offers the opportunity to work on real-world data-driven projects with a focus on innovation and performance.

Key Responsibilities:

• Design, build, and deploy machine learning models and AI-driven solutions.
• Write clean and efficient Python code for data preprocessing, model training, and evaluation.
• Work with large datasets to extract insights and create predictive models.
• Collaborate with cross-functional teams including data scientists, engineers, and business stakeholders.
• Deploy models into production using REST APIs or cloud services.
• Monitor and retrain models to ensure accuracy and efficiency over time.
• Research and experiment with new algorithms and AI techniques

Required Skills and Qualifications

• 2–5 years of hands-on experience in Python development with a focus on AI/ML.
• Solid understanding of machine learning algorithms (supervised, unsupervised, deep learning).
• Experience with ML libraries such as Scikit-learn, TensorFlow, PyTorch, Keras, or XGBoost.
• Proficient in data handling using Pandas, NumPy, and data visualization tools like Matplotlib or Seaborn.
• Experience in training, evaluating, and tuning models using appropriate metrics.
• Strong foundation in mathematics and statistics (linear algebra, probability, optimization).
• Familiarity with REST APIs and model deployment strategies.
• Experience with Git and collaborative development

Preferred Qualifications:

• Bachelor's or master’s degree in computer science, Data Science, AI, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, GCP) and ML Ops tools.
• Exposure to Natural Language Processing (NLP), Computer Vision, or Recommendation Systems.
• Knowledge of Big Data tools (Spark, Hadoop) is a plus.
• Understanding of CI/CD pipelines and containerization using Docker/Kubernetes