Senior Machine Learning Engineer

Title: Senior Machine Learning Engineer, Media GenerationLocation: RemoteCompensation: Up to $300,000 + EquityWe’re partnered with a well-funded startup at the forefront of media generation and digital identity, building the infrastructure for the next generation of interactive, AI-powered experiences. Their platform enables developers and creators to generate fully customizable characters, digital assets, and AI companions, positioning them at the intersection of generative AI, gaming, and social platforms.This is a high-impact role within a growing R&D team, focused on building cutting-edge machine learning systems for media generation. You’ll work on models that power character creation, digital fashion, and interactive experiences, helping define how users create and express themselves in digital environments.What You’ll DoDesign, train, and deploy ML models for high-quality image, video, and 3D asset generationWork across computer vision and graphics to generate meshes, textures, and motionBuild and optimize generative models such as diffusion, GANs, and transformer-based architecturesIntegrate ML systems into user-facing creative tools and applicationsCollaborate with product, engineering, and creative teams to ship AI-powered featuresManage ML infrastructure including datasets, experiments, and deployment pipelinesStay up to date with emerging research and apply new techniques to production systemsRequirementsMaster’s degree or higher in Computer Science, Machine Learning, Computer Vision, or related field3+ years of experience in machine learning, computer vision, or computer graphicsStrong Python skills and experience with frameworks such as PyTorch or TensorFlowExperience with generative models (diffusion, GANs, VAEs) and modern architectures (Transformers, ViTs, etc.)Solid understanding of 3D graphics, computational geometry, or related areasExperience working in cross-functional teams and communicating technical concepts clearlyNice to HaveExperience with 3D reconstruction, tracking, or geometry analysisFamiliarity with neural rendering techniques such as NeRF or Gaussian SplattingExperience scaling ML models and optimizing training pipelinesBackground in distributed training, data pipelines, and experiment trackingPublications or contributions to research or open-source projectsIf you're interested in building next-generation generative AI systems at the intersection of media, gaming, and identity, this is a unique opportunity to help shape a rapidly emerging space.