About the Role
Rockstar Games is seeking a skilled Senior Machine Learning Engineer with strong software development skills and a passion for games, big data, and Machine Learning. You will join a team that builds Data Science products that directly influence game design, live operations, and player engagement at scale. This is a full-time, in-office position based out of Rockstar’s NYC headquarters in Downtown Manhattan.
What We Do
- The Rockstar Games Analytics team provides insights and actionable results to a wide variety of stakeholders across the organization in support of their decision making.
- We partner with multiple departments across the company, leveraging analytics to measure and improve on the success and health of our games.
- We collaborate as a distributed team to develop innovative data pipelines, data products, data models, reports, analyses, and machine learning applications.
- The Machine Learning Engineering vertical within the Analytics team is tasked with designing, building, and deploying ML systems in addition to advising other verticals on how to design and build reliable, scalable and, fit for purpose models.
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.
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.
Pluses
- Production experience deploying Databricks Genie AI and other Databricks Agentic solutions.