Databricks & MLOps Engineer

Vidushi Infotech; United States; Remote; USD 12,000 - 25,000; Full time

Job summary

Vidushi Infotech seeks a Databricks & MLOps Engineer to serve as the Databricks Technical Lead for a client program. You will collaborate with migration and delivery teams to ensure successful adoption, governance, and long-term sustainability of the Databricks platform.

The role requires strong expertise in MLOps, ML engineering, Databricks, ML model deployment, and automated ML pipelines, with a focus on scalable, production-ready solutions.

Qualifications

• 5–8 years of software or ML engineering experience.
• MLOps experience of at least 2 years.
• Experience leading technical initiatives is a plus.

Responsibilities

• Act as the technical lead for Databricks within the client program.
• Provide governance, guidance, and implementation support for Databricks adoption.
• Ensure onboarding and migration of assets to the Databricks platform.
• Design and develop Databricks-native data and ML pipelines.
• Build and maintain automated ML pipelines with triggers for refresh/retraining.
• Establish MLOps best practices across the ML lifecycle.
• Deploy and manage ML models in production using MLOps frameworks.
• Bridge migration and delivery teams to ensure consistent architecture.

Skills

Databricks

MLOps

ML Engineering

ML Pipelines

Leadership

Tools

Databricks

Job description

Databricks & MLOps Engineer

• Experience: 5 to 8 Years
• MLOps Experience: Minimum 2 Years
• Location: Remote India

Role Overview

We are looking for an experienced Databricks & MLOps Engineer to serve as the Databricks Technical Lead for a client program.

The candidate will work closely with the migration and delivery teams, providing technical guidance, governance, implementation support, and hands-on expertise to ensure successful adoption and long-term sustainability of the Databricks platform.

The role requires strong experience in MLOps, ML Engineering, Databricks, ML model deployment, and automated ML pipelines.

Key Responsibilities

• Act as the technical lead for Databricks within the client program.
• Partner closely with the migration team to provide technical guidance, governance, and implementation support.
• Ensure successful onboarding and migration of existing assets to the Databricks platform.
• Design and develop Databricks-native data and ML pipelines.
• Build and maintain automated ML pipelines with scheduled triggers for model refresh and retraining.
• Establish and implement MLOps best practices across the ML lifecycle.
• Deploy and manage ML models in production using appropriate MLOps frameworks and tools.
• Assess business and technical requirements and translate them into scalable ML engineering solutions.
• Ensure ML models are production-ready, maintainable, and scalable.
• Work as a bridge between migration and delivery teams to ensure consistent architecture and effective platform utilization.
• Provide coaching, technical guidance, and hands-on support to the existing engineering team.
• Contribute to the governance, architecture, performance, and long-term sustainability of the Databricks ecosystem.
• Troubleshoot and resolve issues related to ML pipelines, model deployment, and Databricks workloads.