Python-ML-MLOps

Responsibilities

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.

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

• PYTHON
• IOT Analytics – Machine Learning

Educational Requirements

MCA,MSc,MTech,BCA,BSc,BTech