Senior ML Engineer

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

Responsibilities:

• Build and increase customer data science workloads and apply the best MLOps practices 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 areas such as architecture, tooling, and best practices.

Requirements:

• 6+ 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.
• Experience working with Apache Spark to process large-scale distributed datasets.
• Experience working with the Databricks platform.