Senior Machine Learning Engineer, GenAI Data

Workman Labs; San Mateo (CA); Hybrid; USD 243,000 - 295,000; Full time

Job summary

Workman Labs in San Mateo, CA, is seeking a Senior Machine Learning Engineer to build the data flywheel for GenAI foundations like VideoGen and 3DGen. You will architect petabyte-scale data pipelines, synthetic data generation, evaluation frameworks, and inference APIs in a hybrid work setting.

Ideal candidates have 8+ years in data systems engineering, strong Python, and experience with Spark, Ray, Kubeflow, and S3. Collaboration with researchers and MLOps familiarity are a plus.

Qualifications

• 8+ years as a research-focused data systems engineer.
• Experience building scalable ML data pipelines for batch and real-time.
• Strong Python for automation and tooling.
• Experience with cloud data platforms and distributed processing (Spark, Ray, Kubeflow, S3).
• Nice to have: MLOps tools and game dev/3D data tooling.

Responsibilities

• Architect and maintain automated pipelines for ingestion, cleaning, and pre-processing of multi-modal datasets (video, 3D) spanning petabytes of data.
• Leverage image and video generation models to scale multi-modal synthetic datasets.
• Partner with research teams to create training data and synthetic data pipelines.
• Build and own evaluation with metrics and human-in-the-loop interfaces.
• Design and optimize high-throughput, low-latency inference APIs.
• Participate in literature reviews to identify optimizations in generative modeling.
• Implement monitoring for pipeline health and optimize data loading for GPU efficiency.

Skills

Python programming

Data pipelines

MLOps

Cloud data platforms

Big data

Education

Bachelor's degree or equivalent in Computer Science / Computer Engineering

Tools

Spark

Ray

Kubeflow

S3

C++

Job description

Senior Machine Learning Engineer, GenAI Data

Senior engineer on Roblox's Foundation AI organization building the data flywheel behind its VideoGen and 3DGen foundation models — architecting petabyte-scale multi-modal data pipelines, synthetic data generation, evaluation frameworks, and inference APIs.

$243,290 – $295,250 / yr

Location

San Mateo, CA

Hybrid

Seniority

Senior

Compared with 41 other Engineering roles: Common across similar roles Unique to this role

What you'll do

Responsibilities

• Architect and maintain automated pipelines for ingestion, cleaning, and pre-processing of multi-modal datasets (video, 3D) spanning petabytes of data
• Leverage image and video generation models to scale multi-modal synthetic datasets
• Partner with research teams to create training data for research experiments — research and implement synthetic data creation pipelines
• Build and own evaluation — automating heuristic-based metrics and human-in-the-loop interfaces to benchmark training datasets and in-house foundation models
• Design and optimize high-throughput, low-latency inference APIs for internal and external consumer access
• Participate in literature reviews and paper reading groups to identify and implement the latest optimizations in generative modeling
• Implement monitoring for pipeline health and optimize data loading to ensure GPUs are used efficiently

What you'll need

Experience

• 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 batch and real-time environments; experience processing very large datasets (petabytes or more)
• Versatile generalist comfortable with several languages and technologies Unique
• Collaborative team member who mentors peers and takes ownership of key features and projects across team boundaries Unique
• High-quality Python for automation, tooling, and infrastructure management
• Experience with cloud data platforms and distributed processing technologies (e.g., Spark, Ray, Kubeflow, S3)
• Passion for 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 Common
• Nice to have: MLOps (Weights & Biases, MLflow), human-in-the-loop data labeling tools for video/3D, C++ for data loader performance, and game dev / DCC tools (Roblox, Blender, Unreal Engine, Unity)