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.
- 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

📌 MLOps Engineer (Bengaluru)
🏢 Nameless
📍 Bengaluru