Machine Learning Engineer

  • Bengaluru
  • Quantzig

About Quantzig:

Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. we have assisted our clients across the globe with end-to-end advanced analytics, visual storyboarding, Machine Learning, and data engineering solutions implementation for prudent decision making. We are a rapidly growing organization that is built and operated by high-performance champions If you have what it takes to be the champion with business and functional skills to take ownership of an entire project end-to-end, help build a team with great work ethic and a drive to learn, you are the one we’re looking for. The clients love us for our solutioning capability, our enthusiasm and we expect you to be a part of our growth story.


Please find the job description below.


Experience: 3 to 5 Yrs

Notice Period- Immediate Joiner only


Technical Skills:

  • Use Case Migration: Migrate various use cases (housed on Python or Databricks, PySpark) to a centralized machine learning platform on Databricks . Good to have familiarity with Databricks Unity Catalog as an operating interface
  • Python Proficiency: Utilize strong proficiency in Python for data analysis and process development. Understand and replicate existing Python code/logic on the new platform in PySpark for faster processing.
  • PySpark Expertise: Leverage PySpark for data processing and manipulation on Databricks.
  • Azure Familiarity: Apply knowledge of Azure cloud services for data migration. Recommend optimal workflows leveraging Azure cloud services.
  • Kubernetes: Work with Kubernetes for workflow monitoring, scheduling, and related tasks.
  • Code Management: Manage code using GIT for version control and collaboration.
  • Data Pipeline and SQL: Develop and maintain data pipelines, and use SQL for data extraction and model consumption.
  • Workflow Orchestration: Use Apache Airflow to orchestrate and manage workflows.
  • Independence: Work independently without handholding. Set expectations with clients and proactively communicate updates on gaps and project progress.