Python-ML-MLOps

Responsibilities :

Required Skills & Qualifications: 3â€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.

Additional Responsibilities:

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.

Technical and Professional Requirements:

Primary skills:Technology- Internet of Things (IOT)- IOT Analytics - Machine Learning,Technology- Machine Learning- Python