Middle Machine Learning Engineer
1 день назад
About the Role:
We're looking for a mid-level AI Engineer to help test, deploy, and integrate cutting-edge generative AI models into production experiences centered around human avatars and 3D content. You'll work directly with the CEO to turn R&D prototypes into stable, scalable products.
Responsibilities:
- Experiment with and evaluate generative models for:
- Human avatar creation and animation;
- 3D reconstruction and modeling;
- Gaussian splatting–based pipelines;
- Generalized NeRF (Neural Radiance Fields) techniques.
- Build and maintain Python-based tooling for data preprocessing, training, evaluation, and inference.
- Design and optimize cloud-based deployment workflows (e.g., containers, GPUs, inference endpoints, job queues).
- Integrate models into user-facing applications in collaboration with product, design, and frontend teams.
- Monitor model performance, reliability, and cost; propose and implement improvements.
- Stay up-to-date on relevant research and help prioritize which techniques to test and adopt.
Required Qualifications:
- 3–5+ years of experience as an ML/AI Engineer or similar role.
- Strong Python skills and experience with one or more deep learning frameworks (PyTorch preferred).
- Hands-on experience with deploying ML models to cloud environments (AWS, GCP, Azure, or similar) including containers (Docker) and basic CI/CD workflows.
- Familiarity with 3D data formats and pipelines (meshes, point clouds, volumetric representations, etc.).
- Practical exposure to one or more of the following (professional or serious personal projects):
- NeRFs or NeRF-like methods;
- Gaussian splatting / 3D Gaussian fields;
- Avatar generation / face-body reconstruction / pose estimation;
- Comfort working in an iterative, fast-paced environment directly with leadership (reporting to CEO).
- Experience with real-time rendering pipelines (e.g., Unity, Unreal, WebGL) or GPU programming (CUDA).
- Experience optimizing inference performance and cost (model distillation, quantization, batching)
- Background in computer vision, graphics, or related fields (academic or industry).
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