Python-ML-MLOps Professional

Job description

Educational Requirements - BTech - BCA - BSc - MCA - MTech - MSc Service Line Data Analytics Unit Responsibilities - 35 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 Preferred Skills - Technology- >AI-Data science- >PYTHON - Technology- >AI-Physical AI-IOT- >IOT Analytics - Machine Learning