MLOps Engineer

This role is for one of the Weekday's clients

Min Experience: 3 years

Location: Bangalore

JobType: full-time

We are seeking an experienced MLOps Engineer to design, orchestrate, and manage end-to-end machine learning pipelines on modern cloud platforms. This role requires strong expertise in MLOps practices, backend development, and cloud-based deployment, ensuring scalable, reliable, and production-ready ML solutions.

Key Responsibilities

• Build and manage ML pipelines across the full lifecycle: data/feature engineering, model training/inference, and real-time/batch processing.
• Work extensively with Azure and Databricks platforms to enable scalable ML solutions.
• Develop backend services and APIs using FastAPI to support ML workflows.
• Implement MLOps best practices, including monitoring data drift, model drift, and online learning.
• Collaborate with data engineers, data scientists, and cross-functional stakeholders to deliver business-focused ML solutions.
• Use Python, PySpark, and T-SQL for development and data orchestration.
• Set up and maintain CI/CD workflows with GitHub Actions for continuous integration and deployment.
• (Good to have) Contribute to deployment and monitoring of LLM-based GenAI solutions.

Qualifications

• 3–5 years of relevant experience as an MLOps Engineer.
• Strong hands-on expertise in MLOps, Python, PySpark, Azure Databricks, and CI/CD pipelines.
• Knowledge of backend frameworks (FastAPI) and modern cloud-based ML deployments.
• Strong problem-solving, debugging, and collaborative skills.

Skills

• Core: MLOps, Python, PySpark, T-SQL, Azure Databricks, CI/CD (GitHub Actions), FastAPI
• Preferred: LLM-based GenAI deployment