[2026] Senior Machine Learning Engineer, AI Platform - PhD Early Career
Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.
At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
The Foundation AI Group is on a mission to establish Roblox as the standard for 3D foundational models (3DFMs), democratizing creation by making it simple for anyone to generate high-quality, immersive 3D experiences using AI. The AI Platform team is a foundational part of this vision, supporting hundreds of ML use cases and billions of inferences daily across Discovery, Safety, Engine, and more. We are seeking exceptional PhD new graduates to drive innovation across three critical areas: AI Platform, Distributed Inference Systems, and Generative AI Information Retrieval.
You Will
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As a Senior Machine Learning Engineer on the AI Platform team, you will be a key contributor to building the cutting-edge systems that power AI at Roblox. You will focus on one of three high-impact tracks:
Track 1: AI Platform Projects
- Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox.
- Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.
- Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable.
Track 2: Distributed Inference & Systems Optimization
- Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.
- Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.
Track 3: Information Retrieval & RAG for Gen AI
- Lead the design and development of Retrieval-Augmented Generation (RAG) systems.
- Build and maintain core information retrieval infrastructure—vector databases and knowledge graphs—to enable accurate grounding of Gen AI models.
- Ship language models and 3D objects as a service for the Roblox community, making creation easier.
You Have
- Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.
- Experience with high performance distributed systems, ML Infrastructure, LLM fine tuning/RL, Information Retrieval and Gen AI context generation.
- Expertise in one or more of the following key areas:
- AI/ML Platform Data stores - Features stores, Vector DBs and Knowledge Graphs.
- LLMs - Fine tuning, Safety.
- Agentic systems - Agent evaluation, context engineering.
- Experience building agentic applications with context for real world applications.
- Collaborative mindset and experience integrating and deploying optimized models with cross-functional teams, including data scientists and software engineers.
- Experience with graph databases and large-scale GNNs (Graph Neural Networks)
- Experience working with Kubernetes
- Experience working with one or more cloud providers (e.g., AWS, Azure, GCP)
- Experience working with high availability systems
- Experience working with ML models, LLMs or other AI systems
You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.
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For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion