A mid-level Python developer (2-3 years) who designs, builds, and deploys AI/ML-powered applications: integrating ML models into production, developing REST APIs for AI services, and running data pipelines. Core stack includes Python, TensorFlow/PyTorch/scikit-learn, Flask/FastAPI, Docker, CI/CD, and cloud AI platforms (AWS SageMaker, Azure ML, GCP).
We are seeking a skilled Python Developer with expertise in Artificial Intelligence and Machine Learning to join our dynamic team. The ideal candidate will design, develop, and deploy AI-powered applications, pipelines, and solutions, ensuring performance, scalability, and maintainability in production environments.
Total Experience : 2-3 year
Key Responsibilities:
- Design, develop, test, and deploy scalablePython applications.
- Write clean, efficient, and modular code integratingAI/ML modelsinto production systems.
- DevelopREST APIsforAI servicesand manage data pipelines forML workflows.
- Build, train, evaluate, and optimizemachine learning modelsusing libraries such asTensorFlow,PyTorch, or scikit-learn.
- Deploy models using ML frameworks or cloud-based AI services(AWS SageMaker, Azure ML, or GCP AI Platform).
- Conduct feature engineering,model selection, hyperparameter tuning,and performance evaluation.
- Work with structured and unstructured data(CSV, JSON, images, text, etc.).
- Developdata preprocessing pipelinesensuring data quality and readiness for modelling.
- Participate in code reviews, design discussions, and agile ceremonies (stand-ups, sprint planning).
- Stay updated with the latest AI/ML trends, architectures, and algorithms.
- Containerize applications usingDocker.
- Deploy AI models in production usingCI/CD pipelines.
Required Qualifications:
- Bachelor’s or Master’s degree inComputer Science, Data Science, AI, or related fields.
- 2-3 yearsof hands-on experience in Python development.
- Strong understanding ofAI/ML concepts, algorithms, and workflows.
- Experience withmachine learning libraries(TensorFlow, PyTorch, Keras, scikit-learn).
- Proficiency indata manipulation libraries(Pandas, NumPy) and visualization tools (Matplotlib, Seaborn).
- Experience deploying AI models into production systems.
- Familiarity withAPI developmentusing frameworks like Flask or FastAPI.
- Understanding ofSQL and NoSQL databases.
- Experience inNatural Language Processing (NLP)orComputer Vision (CV)projects.
- Knowledge ofMLOps practices, ML model monitoring, and continuous training.
- Familiarity withbig data tools(Spark, Hadoop) is a plus.
- Working experience withcloud platforms(AWS, Azure, GCP) for AI services.
- Exposure toDeep Learning architectures(CNNs, RNNs, Transformers).