Educational Requirements

- Bachelor of Engineering

Responsibilities

- Strong Python programming

- Hands-on experience in Machine Learning workflows

- Experience with MLOps tools: MLflow / Kubeflow / Airflow / SageMaker / Vertex AI

- Knowledge of CI/CD tools (GitHub Actions, Jenkins, etc.)

- Experience deploying models using: Docker, REST APIs, Flask/FastAPI

- Understanding of: Model versioning

- Experiment tracking

- Model monitoring

Additional Responsibilities

- Experience with real-time inference systems

- Exposure to monitoring tools (Prometheus, Grafana)

- Knowledge of LLM deployment / RAG pipelines

Technical and Skilled Requirements

- Exposure to cloud platforms (AWS / Azure / GCP) for ML deployment

- Knowledge of LLMOps / GenAI deployment pipelines

- Familiarity with: Feature stores

- Data pipelines (Spark, Kafka)

- Experience with Kubernetes (basic deployment level)

Preferred Skills

- Analytics- >Data Science

- Technology- >AI-Data science- >Data Science - Basic

- Technology- >AI-Generative AI- >Generative AI - Basic

📌 MLOps Engineer (Bengaluru)
🏢 Infosys
📍 Bengaluru