Your responsibilities will include:

• Prototyping apt technical solutions and finding best fits for the context engine.
• Architecting and building the core Context Platform.
• Designing schemas and primitives for Decision Memory and enterprise context.
• Owning context storage systems (graph, vector, event/time-based).
• Building read/write/query APIs used by agents, products, and external apps.
• Designing permission-aware, auditable context access.

You will be working closely with agentic systems engineers and product leadership to ensure the context engine is interoperable, portable, and zero-lock-in by design.

In this role, you will own:

• Context schemas and schema evolution strategies.
• Storage and data modeling choices.
• Platform APIs and interfaces.
• Security, identity propagation, and audit foundations.
• Long-term scalability and correctness of context data.

You will not own:

• Agent behavior or orchestration logic.
• Business rules or governance policy decisions.
• Product UI or workflow automation.

The ideal candidate will have significant experience building distributed systems, data platforms, or infrastructure, and will be comfortable operating in ambiguous, greenfield problem spaces. They will also have deep expertise in data modeling and schema design, experience designing shared platforms used by many teams, and strong instincts around APIs, contracts, and backward compatibility.

Nice to have experience with knowledge graphs, metadata systems, or search/retrieval systems, experience building systems with governance, auditability, or compliance requirements, and familiarity with dbt or modern analytics stacks or developer tooling.

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San Mateo, CA, United States

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.

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.

You Will

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.

As you apply, you can find more information about our process by signing up for Speak\_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.

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.

Annual Salary Range

$195,780—$242,100 USD

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

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What you'll do

• Develop AI-based foundations and services that allow the Frostbite community to benefit from agentic developer workflows.
• Provide secure and scalable solutions for all stages of the software development lifecycle, including spec-driven coding, validation and releasing.
• Pilot new AI capabilities to assess their impact on developer efficiency and quality.

What you need

• 4+ years of job experience in a hands-on coding role using languages like Python, C# or C++.
• 1+ years of experience using generative AI software engineering solutions such as GitHub CoPilot.
• Proficiency in good development practices (version control, code reviews) and validation (static code analysis, unit testing, CI/CD pipelines).

Why this matters

This role is a key part of Electronic Arts' efforts to transform software engineering and quality processes with the power of generative AI, agents and context engineering. By contributing to this work, you will have a direct impact on the quality and efficiency of game development at Electronic Arts.

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Deine Themenschwerpunkte sind... Aufbau und Analyse von Knowledge Graphen Unterstützung bei GenAI- und LLM-basierten Use Cases Durchführung von Machine-Learning- und Data-Science-Analysen Optimierung unseres Retrieval- und Datenverarbeitungsprozesses Planung und Umsetzung technischer Analysen und Prototypen Mitwirkung in wissenschaftlichen Innovationsprojekten

What you need

Ein Studienplatz für Informatik, Data Science, Wirtschaftsinformatik, Mathematik oder eines vergleichbaren Studiengangs (mindestens im 3. Semester oder im Gap Year zwischen Bachelor und Master) Sicherer Umgang mit Python und grundlegende Erfahrung in Data-Science- oder Machine-Learning-Workflows Grundkenntnisse in Cloud-Architekturen (bevorzugt Azure) oder Interesse, diese im Praktikum aufzubauen Erste Berührungspunkte mit Themen wie Datenanalyse, Wissenmodellierung, Knowledge Graphs oder Machine Learning von Vorteil Eine selbstständige, analytische und strukturierte Arbeitsweise Freude an Forschung, neuen Technologien und interdisziplinärer Zusammenarbeit Ein sicherer Umgang mit MS Office Sehr gute Deutsch- und gute Englischkenntnisse (min. B2)

Why this matters

Wir als Unternehmen "Am Anfang schaute ich mich um, konnte aber den Wagen, von dem ich träumte, nicht finden. Also beschloss ich, ihn mir selbst zu bauen." Dieser Satz von Ferry Porsche bringt alles auf den Punkt, was Porsche ausmacht. Mitarbeiter, die so denken, stoßen bei uns immer auf offene Türen.

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