Job Overview
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Job Description
About Runway and Our Mission
We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world.
World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached.
Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.
About The Role
We're looking for a Data Engineer to build and scale the data infrastructure that powers Runway's AI research and business intelligence. You'll own critical data pipelines spanning production databases, analytics warehouses, and large-scale ML training datasets. This role sits at the intersection of data engineering, ML infrastructure, and analytics—you'll enable both world-class research and data-driven business decisions.
You'll work on challenging problems at scale: managing billions of rows of multimodal training data, building CDC streams from production systems, optimizing vector databases for ML workflows, and creating the foundational data layer that the entire company relies on.
Technical Stack
Our data infrastructure spans multiple specialized systems: LanceDB for vector storage and dataset versioning with multimodal training data, ClickHouse as our analytics warehouse receiving CDC streams from production Postgres via AWS Kinesis, and BigQuery for training run logs and evaluation results. We use Ray for large-scale distributed data processing on managed Kubernetes clusters, handling preprocessing, feature generation, and dataset curation at scale.
We're actively building out our data platform—introducing dbt for standardized transformations, improving dataset versioning and data lineage tracking, scaling data sourcing pipelines, and establishing better data quality practices. We use Prometheus and Grafana for monitoring, and Terraform for infrastructure management. This is an opportunity to bring best practices and technical leadership as we mature our data infrastructure to support rapidly growing ML training and research needs.
What you’ll do
- Build and own pipelines for the creation, curation, and processing of large-scale multimodal datasets, including vector database (LanceDB) management and query optimization for ML metadata.
- Build and own ETL and CDC streams from Postgres and ClickHouse to analytics warehouses.
- Build standardized data transformation layers using dbt to replace ad-hoc SQL queries and create maintainable data models for business analytics.
- Manage production databases (Postgres, ClickHouse) and optimize for performance and reliability.
What You’ll Need
- 4+ years of industry experience in data engineering.
- Strong knowledge of Python.
- Experience with data quality, deduplication, and cleaning at scale.
- Comfortable working with cloud storage (S3) and managing large datasets.
- Experience building and maintaining ETL/CDC pipelines at scale.
- Strong SQL skills and experience with multiple database systems (Postgres, columnar databases like ClickHouse/Redshift).
- Humility and open mindedness; at Runway we love to learn from one another.
Nice to Have
- Experience with one or more frameworks for large-scale data processing (e.g. Spark, Ray, etc) and one or more ML frameworks (e.g. PyTorch, JAX).
- Knowledge of cloud platforms (AWS, GCP, or Azure) and their data service offerings.
- Knowledge of data privacy and data security best practices.
- Experience with business intelligence and visualization tools (e.g., Looker, Tableau, PowerBI, Metabase, or similar).
- Experience in a high-growth startup environment or similar fast-paced setting.
Salary Range
$240,000-290,000
Working at Runway
Great things come from great teams. We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.
More about Runway
- Universal World Simulator
- GWM-1Gen-4.5
- General World Models
- Robotics SDK
- Conversational Real-time Agents
- Runway Studios
We're excited to be recognized as a best place to work:
Crain's | InHerSight | BuiltIn NYC | INC
Key skills/competency
- Data Engineering
- Python
- SQL
- ETL/CDC Pipelines
- Cloud Storage (S3)
- Databases (Postgres, ClickHouse)
- Data Quality
- Large-Scale Data Processing
- ML Infrastructure
- dbt
How to Get Hired at Odyssey Logistics
- Tailor your resume: Highlight your 4+ years of data engineering experience, Python proficiency, and SQL skills. Quantify achievements in ETL/CDC pipeline development and large dataset management.
- Showcase relevant tech: Emphasize experience with Postgres, ClickHouse, LanceDB, dbt, cloud storage (S3), and large-scale processing frameworks like Ray or Spark.
- Craft a compelling cover letter: Express your passion for AI and world models. Connect your experience to Runway's mission and the specific responsibilities of the Data Engineer role.
- Prepare for technical interviews: Expect questions on data modeling, pipeline design, SQL optimization, Python coding, and your approach to data quality and scalability.
- Demonstrate cultural fit: Highlight your humility, open-mindedness, and eagerness to learn and collaborate with a fast-paced startup team.
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