Hedra is looking for an ML Engineer to design, build, and maintain data pipelines at scale to support the company's ML efforts, focusing on deployment and scalability for their generative media platform.
Requirements
- Experience with cloud computing platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure, essential for managing large-scale ML workloads.
- Understands the importance of orchestration tools in ML data workflows, and values engineering processes and version control (CI/CD).
- Experience designing, building, and managing large-scale data pipelines for ML; experience with video data is a huge plus.
- Understanding of distributed training techniques and how to scale models across multi-node clusters aligning with video generation needs.
Responsibilities
- Lead the efforts to design, implement, and maintain scalable solutions for data warehousing and processing.
- Manage and optimize the performance of our computing clusters or cloud instances, such as AWS or Google Cloud, to support distributed data processing at scale.
- Design data snapshots, ETL pipelines, and storage solutions with a strong focus on data shape and layout to ensure the flexibility required for training
- Collaborate across research teams to understand their data needs and provide appropriate solutions, facilitating seamless model training.
Other
- 3+ YOE designing, building, and maintaining data pipelines at scale.
- Bachelor’s degree in Computer Science, Information Technology, or a related field.
- Strong problem-solving and communication skills, given the need to collaborate with diverse teams.
- We encourage you to apply even if you don't meet every requirement — we value curiosity, creativity, and the drive to solve hard problems.
