MLOps Engineer

Summary

I'm a Columbia Engineering graduate currently working in my new grad role, with a year of experience working on lower-level tech infrastructure. The course I enjoyed most at Columbia was Distributed Systems, with a capstone project of developing a robust and fault-tolerant(sharded, based on a Paxos implementation) distributed key-value store. I'm interested in solving complex problems that allow processes to scale efficiently (in terms of time and cost), and enjoy leveraging software tools to extract the best utility from any resources at hand. I've worked plenty with several cloud technologies in my internships and schoolwork, including Databricks, AWS, Terraform, Apache Spark and Airflow. One of my most interesting recent projects was leading my team's efforts to transition from Spark to Databricks under the guidance of our principal engineer. This involved plenty of prototyping with key ML pipelines to first determine the feasibility of the transition, as well as comparing several pathways that Databricks offered ranging from easy-to-use high-level CLI tools to lower-level SDKs. In the future, I'm excited to continue my career in developing high-performing robust systems.

Expectations

Plenty of growth opportunities, challenging work, and a collaborative culture. I'm interested in lower-level work, especially ML infrastructure or traditional tech infrastructure roles. I'm interested in all domains, but especially working in defense, health, or B2B tech. I'm also interested in security roles.

Employment Preferences

Expected Base Salary

**0,000 USD

Academic Degree

Experience

Skills

• C
• C++
• Databricks
• Spark
• Bash
• Python
• MLOps
• Tech Infrastructure
• Devops