Job Title: Python Developer – AI/ML & Data Science
Experience: 4–7 Years
Responsibilities
- Develop, optimize, and maintain Python-based applications with strong integration of Django frameworks .
- Design, build, and deploy AI/ML models (supervised, unsupervised, deep learning) for real-world applications.
- Perform data preprocessing, feature engineering, and model training to enhance performance and accuracy.
- Work with large-scale datasets using Big Data frameworks (Hadoop, Spark, Databricks, etc.).
- Build and manage end-to-end data pipelines (ETL/ELT) for scalable and reliable workflows.
- Implement MLOps practices (CI/CD pipelines, model deployment, monitoring, retraining).
- Conduct data modeling, database design, and performance tuning for analytics and applications.
- Develop dashboards, APIs, and visualization tools to deliver insights and integrate AI/ML solutions into products.
- Collaborate with cross-functional teams (engineering, product, and business) to design and implement data-driven, scalable solutions .
- Continuously explore and adopt new AI/ML techniques, Python libraries, and cloud services to optimize solutions.
Requirements & Skills
- Proven experience (4–7 years) in Python development with frameworks like Django/Flask .
- Hands-on expertise in AI/ML model design, development, and deployment using libraries like Scikit-learn, TensorFlow, or PyTorch.
- Strong understanding of data preprocessing, feature engineering, and model optimization techniques .
- Experience with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes, CI/CD pipelines).
- Proficiency in SQL, data modeling, and database design (RDBMS & NoSQL).
- Familiarity with big data frameworks (Hadoop, Spark, Databricks) and distributed computing.
- Strong knowledge of statistics, mathematics, and data science concepts .
- Experience building REST APIs, dashboards, or services to integrate ML models into applications.
- Excellent problem-solving skills with an analytical and research-driven mindset.
- Strong communication skills to present insights and collaborate with stakeholders.
- Education: Bachelor’s/Master’s in Computer Science, Data Science, or related field.