Python-ML-MLOps

Required Skills & Qualifications:

3–5 years of experience in Python development for data/ML applications. Strong understanding of Machine Learning algorithms (supervised, unsupervised, NLP, etc.). Hands-on experience with ML libraries/tools:

Scikit-learn, TensorFlow, PyTorch, XGBoost

Experience in building and managing ML pipelines. Solid knowledge of MLOps concepts:

Model versioning (MLflow, DVC) CI/CD pipelines Model deployment & monitoring

Experience with REST APIs (FastAPI/Flask). Strong knowledge of data structures, algorithms, and statistics. Experience with SQL and NoSQL databases.

Experience with cloud platforms (AWS, Azure, or GCP). Hands-on with MLOps tools:

MLflow, Kubeflow, Airflow, SageMaker, Vertex AI

Knowledge of Docker & Kubernetes. Experience with big data tools (Spark, Hadoop). NLP, Computer Vision, or Deep Learning specialization. Familiarity with Data Engineering pipelines.