Description

You will design and implement scalable data engineering and machine learning solutions for production systems.

Responsibilities

• Develop and deploy machine learning models and algorithms into production environments.
• Build and maintain data pipelines using AWS, Docker, and Airflow.
• Engineer big-data solutions utilizing Databricks, S3, and Spark.
• Write production-level, scalable code for data processing and analysis in Python or Scala.
• Execute effective approaches to solve complex machine learning problems.

Required Skills

• 7+ years of analytical or data engineering experience.
• 7+ years of experience developing ML models and performing data analysis with Python or R.
• 5+ years of experience writing production-level, scalable code in Python or Scala.
• 5+ years of experience developing algorithms for production deployment.
• Deep understanding of modern machine learning, including deep learning and mathematical underpinnings.
• Proficiency with Python, SQL, and AWS.
• Experience with Databricks, S3, and Spark.

Preferred Skills

• MS or PhD in statistics, math, computer science, or a related quantitative field.
• Experience building full-stack ML pipelines: extraction, mining, training, feature development, and deployment.
• Experience with Snowflake, Kafka, or Flink for streaming and cloud-hosted databases.

Key Skills

Education

Any Graduate