Senior Machine Learning Engineer, GenAI Data

Achievements

• High-Scale Data Orchestration: Architect and maintain automated pipelines for the ingestion, cleaning, and pre-processing of multi-modal datasets (video, 3D), spanning petabytes of data
• Synthetic Data Generation: Leverage image and video generation models to scale multi-modal synthetic datasets
• Research-to-Production Bridge: Partner with research teams to create training data for research experiments - research and implement synthetic data creation pipelines
• Scalable Evaluation Frameworks: Build and own evaluation - automating both heuristic-based metrics and human-in-the-loop interfaces to evaluate and benchmark training datasets and in-house foundation models
• Model Deployment & API Architecture: Design and optimize high-throughput, low-latency Inference APIs for internal and external consumer access
• Autonomous SOTA Tracking: Actively participate in literature reviews and paper reading groups to identify and implement the latest optimizations in generative modeling
• Resource Efficiency & Observability: Implement monitoring pipeline health, optimizing data loading to ensure GPUs are used efficiently

Requirements

• 8+ years of experience as a research-focused data systems engineer (preferably working with 3D and video foundation models)
• Expertise in building scalable ML data pipelines for both batch and real-time environments. Experience working with and processing very large datasets (Petabytes or more).
• Versatile: You're a generalist and you are comfortable with several languages and technologies already; you are adaptable in any situation
• Team-Player & Technical Leader: You are a collaborative team member who actively mentors peers, drives technical excellence, and takes ownership of leading and delivering key features and projects across team boundaries
• Python Proficiency: You can write high-quality Python code for automation, tooling, and infrastructure management
• Experience with cloud data platforms and distributed processing technologies (e.g., Spark, Ray, Kubeflow, S3, etc.)
• Passionate about the potential of generative AI, particularly in creative domains like 3D/4D content.
• Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, or a similar technical field

Qualifications

• MLOps Experience: Knowledge of experiment tracking (Weights & Biases, MLflow) and versioning for massive datasets.
• Custom Tooling Development: Experience building internal "human-in-the-loop" tools for data labeling specific to video or 3D.
• C++ Knowledge: Optimize the performance of data loaders and being comfortable modifying engine code.
• Game development and digital content creation tools: Experience with making Roblox games, using Blender, Unreal Engine, or Unity.

Benefits

• Reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.

Pay

• 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.

Schedule

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

Location

• 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.