Machine Learning Engineer, Data at Hedra

About HedraHedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence.At the core of Hedra Studio is our Character-3 foundation model, the first omnimodal model in production. Character-3 jointly reasons across image, text, and audio for more intelligent video generation — it’s the next evolution of AI-driven content creation.At Hedra, we’re a team of hard-working, passionate individuals seeking to fundamentally change content creation and build a generational company together. We value startup energy, initiative, and the ability to turn bold ideas into real products. Our team is fully in-person in SF/NY with a shared love for whiteboard problem-solving.OverviewWe are looking for an ML Engineer with 3+ YOE designing, building, and maintaining data pipelines at scale. The ideal candidate has diverse experience managing data from ingest and processing through storage and training. This role is vital for ensuring the computational backbone supports the company’s ML efforts, focusing on deployment and scalability.ResponsibilitiesLead the efforts to design, implement, and maintain scalable solutions for data warehousing and processing. Capable of providing the right solutions for the evolving needs of our research teams.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 trainingCollaborate across research teams to understand their data needs and provide appropriate solutions, facilitating seamless model training.QualificationsBachelor’s degree in Computer Science, Information Technology, or a related field.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.Strong problem-solving and communication skills, given the need to collaborate with diverse teams.BenefitsCompetitive compensation + equity401k (no match)Healthcare (Silver PPO Medical, Vision, Dental)Lunch and snacks at the officeWe encourage you to apply even if you don't meet every requirement — we value curiosity, creativity, and the drive to solve hard problems.