Machine Learning Engineer

Role Overview

Join a high-impact enterprise data engineering team building scalable Azure-based data platforms that power analytics, reporting, and large-scale data transformation initiatives.

Why This Role Matters

We are on a mission to redefine how organizations leverage Data and AI to drive growth, innovation, and efficiency. Our pioneering products empower businesses to simplify complex workflows, adopt cutting-edge technology, and achieve sustainable scalability.

What You'll Do

• Build and increase customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domains
• Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation
• Advise data teams on several data science such as architecture, tooling, and best practices

Core Technical Requirements

• 3-5 years of hands-on industry data science experience, using typical machine learning and data science tools including pandas, mlflow, scikit-learn, gensim, nltk, and TensorFlow/PyTorch
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP including drift monitoring
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research) or equivalent practical experience

Preferred Qualifications

• Experience working with Apache Spark to process large-scale distributed datasets
• Experience working with the Databricks platform

Requirements

profiles of 4+ and 6+ years exp for senior ML engineer and ML architect