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.
Robust hands-on expertise in MLOps, Python, PySpark, Azure Databricks, and CI/CD pipelines.
Knowledge of backend frameworks (FastAPI) and modern cloud-based ML deployments.
Robust problem-solving, debugging, and team-oriented skills.

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

📌 Mlops Engineer Bengaluru (India)
🏢 Nameless
📍 India