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
.
Solid hands-on expertise in
MLOps, Python, PySpark, Azure Databricks, and CI/CD pipelines
.
Knowledge of backend frameworks (FastAPI) and contemporary cloud-based ML deployments.
Solid 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
🏢 Weekday AI
📍 Bengaluru