Senior Machine Learning Engineer

Rockstar Games•New York, NY

7h•$160,000 - $195,000•Onsite

About The Position

Rockstar Games is seeking a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data, and Machine Learning. This role involves joining a team that builds Data Science products that directly influence game design, live operations, and player engagement at scale. The position is full-time and based in Rockstar’s NYC headquarters. The Rockstar Games Analytics team provides insights and actionable results to various stakeholders, leveraging analytics to measure and improve game success. The Machine Learning Engineering vertical within the Analytics team is responsible for designing, building, and deploying ML systems, as well as advising other verticals on building reliable, scalable, and fit-for-purpose models.

Requirements

5+ years of experience building ML systems in production.
Bachelor’s degree or equivalent in an engineering or technical field such as Computer Science, Mathematics, Statistics, or strong quantitative and software background.
Proven track record in building, monitoring, and optimizing large-scale ML solutions and infrastructure.
Experience working in Databricks and Databricks MLflow is essential.
Experience working with pipeline scheduling tools such as Airflow & Astronomer.
Experience working with CI/CD tools such as Terraform and GitHub.
Ability to push the frontier of technology and freely pursue better alternatives.

Nice To Haves

Production experience deploying Databricks Genie AI and other Databricks Agentic solutions

Responsibilities

Partner with Data Scientists and business stakeholders to understand analytical & ML needs and translate them into robust ML solutions that enable us to leverage and derive insights.
Design and build end-to-end ML pipelines, including data, features, training and, serving.
Push the boundaries of our ML and Data Science platform by taking advantage of and spearheading cutting-edge advancements in AI and Agentic frameworks.
Set up monitoring, A/B testing, and metrics frameworks to measure real impact.
Perform timely Root Cause Analysis to troubleshoot model and data-related issues; assist in implementation of code and process fixes.
Provide thought leadership and collaborate with other team members to continue to scale our architecture to evolve for the needs of tomorrow.
Contribute to the technical strategy and establishment of best practices within the team.
Develop and support CI/CD processes.