Pioneers Latent Space Models to solve core challenges in voice AI, developing neural audio codecs, generative speech models, and scalable multimodal systems. Requires strong expertise in statistical learning, foundation models, and bridging theory to efficient deployment.

Research Engineer develops and experiments with multimodal world models, focusing on data strategies, training techniques, evaluations, and production deployment for AI simulation technologies. Requires 4+ years in ML research/engineering and proficiency in PyTorch or JAX.

Designs and tests zero-knowledge proof systems for biometric likeness verification in privacy-focused identity solutions. Requires expertise in zk-SNARKs/STARKs, cryptography, and prototyping tools like Circom and Semaphore.

We are seeking full-time researchers to develop and analyze learning algorithms for a system that represents domain knowledge as modular probabilistic models. The role involves theoretical problems with immediate implementation applicability in finance and scientific research.

Research Engineer working on frontier audio AI models, including training, post-training, data curation, architectural improvements, and rigorous evaluation. Requires at least 3 years of AI experience and evidence of solving challenging machine learning problems through projects or research.

Designs and develops cutting-edge multimodal AI systems integrating text, speech, and vision. Conducts research on representation learning using Python, JAX, PyTorch, TensorFlow, with expertise in distributed training and autoregressive models.

Applied Research Scientist develops computer vision and generative models for creative AI tools, collaborating cross-functionally to productionize research. Requires 4+ years in ML/CV/graphics, strong Python/C++/PyTorch skills, and experience mentoring researchers.

Leads Applied ML Research team focused on computer vision and foundation models for AI content creation and world simulation. Requires 5+ years research experience, 1+ year managing teams, and skills in productionizing ML research.

Leads research in machine learning, robotics, and AI for autonomous systems, including perception, modeling, and inference. Requires PhD in related field, real-world data experience, and publications in top conferences.