Job Description
Job Summary:
We are seeking a skilled and motivated Python Developer with 4–6 years of professional experience in developing robust applications with a strong focus on Artificial Intelligence (AI) and Machine Learning (ML). The ideal candidate will be responsible for designing, developing, and deploying ML models and data-driven solutions that solve complex business problems. You will collaborate with data scientists, product managers, and engineers to bring innovative AI solutions to production.
Key Responsibilities:
Design, develop, and deploy AI/ML models using Python and ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar. Write efficient, reusable, and testable Python code for backend services, model pipelines, and data processing tasks. Work on data acquisition, cleaning, transformation, and feature engineering. Implement and maintain ML models in production environments using tools such as Docker, Kubernetes, and REST APIs. Collaborate with data scientists to productionize models and optimize performance. Conduct code reviews, write unit tests, and ensure code quality. Work with cloud services (AWS, Azure, or GCP) for model training, deployment, and monitoring. Analyze and interpret large datasets to derive actionable insights and build intelligent solutions. Document processes, model architecture, and maintain reproducibility of experiments.
Required Skills and Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 4 to 6 years of experience in Python development with a focus on AI and ML applications. Strong understanding of ML algorithms, model evaluation metrics, and data science workflows. Experience with data manipulation tools like Pandas, NumPy, and data visualization libraries such as
Matplotlib or Seaborn. Proficiency with ML/DL frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn. Experience building and deploying RESTful APIs and working with microservices architecture. Familiarity with CI/CD pipelines, Git, and containerization tools (Docker, Kubernetes). Working knowledge of SQL and NoSQL databases. Strong problem-solving and communication skills.Preferred Qualifications: Experience with ML Ops tools like MLflow, SageMaker, or Vertex AI. Familiarity with big data platforms like Spark or Hadoop. Contributions to open-source ML projects or GitHub portfolio. Knowledge of NLP, computer vision, or reinforcement learning.