> Markdown version of [/jobs/ext/4669357-machine-learning-engineer-creator-tools-automation](https://www.wearedevelopers.com/jobs/ext/4669357-machine-learning-engineer-creator-tools-automation). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer: Creator Tools & Automation - **Company:** Roblox - **Location:** San Mateo, CA, United States - **Experience:** Expert - **Salary:** $243,290 - $295,250 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, C Sharp (Programming Language), C++ (Programming Language), Python (Programming Language), NoSQL, SQL Databases, Large Language Models, Data Pipelines, Programming Languages - **Published:** November 11, 2026 - **Apply:** https://careers.roblox.com/jobs/8359456?gh_jid=8359456 ## About the Role * 5+ years of experience shipping high-complexity software and supporting mission-critical applications at scale. * Experience architecting, designing, and leading implementation across a wide range of software products and systems. * Experience building AI-powered products in production, including LLM integration, orchestration, reliability, and observability. * Familiarity with agentic systems and multi-step execution loops, including planning, tool use, retrieval, recovery, and long-running workflows. * Understanding of tools, skills, and evaluation frameworks for AI systems, including how to design reliable tool interfaces and measure quality through structured evals. * Experience building data pipelines and turning large-scale behavioral and business data into signals, scores, and recommendations. * Expertise in component-based libraries and frameworks, with a strong grasp of building performant, high-quality user experiences. * Proficiency in C++, C#, Java, Python, or similar programming languages. * Strong understanding of SQL and NoSQL systems at scale. * Comfort working in ambiguity on a new team, partnering closely with product and non-engineering stakeholders to define what gets built.