Research Scientist
Research Scientist developing and deploying large-scale diffusion and generative models for 3D worlds. Requires at least 3 years of generative modeling or applied ML experience, strong Python and deep learning framework expertise, and a record of impactful research or open-source contributions.
About the job
Responsibilities
- Design, implement, and train large-scale diffusion models for generating 3D worlds.
- Experiment with diffusion models to add control signals, adapt models to target aesthetic preferences, and distill models for efficient inference.
- Translate product requirements into technical roadmaps in collaboration with research and product teams.
- Contribute hands-on across data curation, experimentation, evaluation, deployment, and production integration.
- Explore and integrate advances in diffusion and generative AI.
- Mentor colleagues and drive best practices in generative modeling and machine learning engineering.
Requirements
- 3+ years of experience in generative modeling or applied machine learning roles.
- Extensive experience with PyTorch or TensorFlow, particularly diffusion and other generative models.
- Deep expertise in an area such as pre-training, post-training, diffusion distillation, or fine-tuning with new conditioning signals.
- Strong record of publications or open-source contributions involving large-scale diffusion models.
- Strong Python programming skills and experience with GPU-accelerated computing.
- Ability to communicate complex technical concepts and collaborate effectively with researchers and cross-functional teams.
- Comfort working in a dynamic, ambiguous, high-ownership startup environment.
Nice-to-haves
- Experience with large-scale model training.
- Data curation for pre-training or post-training.
- Tokenizers and VAEs for image, video, or 3D data.
- Long-context architectures.
- 3D vision.
- Open-source contributions in computer vision, graphics, or machine learning.
- Familiarity with multi-node GPU clusters and distributed training environments.
- Experience integrating machine learning models into production.
- Experience developing or training large-scale, state-of-the-art generative models.
Skills
Generative Modeling, Diffusion Models, 3D Vision, PyTorch, TensorFlow, Python, Gpu Computing, Computer Vision, Distributed Training, Machine Learning, Data Curation, Tokenizers, Vaes, Long-Context Architectures, 3D Modeling
Similar jobs
AI Research jobs
The Voleon Group
New York, NYConducts causal inference research for financial market prediction and portfolio optimization, developing and validating models from research through live trading. Requires Ph.D.-level coursework, strong causal inference and statistics expertise, mathematical ability, and production Python skills.
Descript
San Francisco, CA
Applied research scientists develop deep-learning and generative media systems for video, audio, and multimodal editing features that ship to millions of users. The role requires strong PyTorch or TensorFlow skills, rapid experimentation, and evidence of impactful research or production machine-learning work.
Snowflake
Bellevue, WA
Develop and optimize production-scale LLM inference systems across distributed runtimes, GPU kernels, scheduling, and model-system co-design. The role requires a bachelor’s degree and at least five years of experience in inference, distributed AI, GPU systems, or high-performance computing.
Baseten
San Francisco, CA
Build and ship agentic AI product experiences, internal automation, and customer-facing features across the stack. The role requires 5+ years of software engineering experience, hands-on experience with AI or LLM-powered products, Python proficiency, and strong autonomy.
AfterQuery
San Francisco, CA
Designs, validates, and publishes rigorous evaluations and benchmarks for frontier AI systems across agentic, coding, safety, and expert-domain applications. The role requires strong research publication experience, scientific writing, experimental rigor, and the ability to deliver reproducible evaluation systems.