AI Engineer

LiveX AI is building real-time, interactive AI avatars, where generative models must perform reliably in live settings. This AI/Machine Learning Engineering role focuses on taking models from training and evaluation through deployment, with a strong emphasis on low-latency inference for streaming experiences. Based in Palo Alto, CA, the position is onsite.

What you’ll do

• Train and fine-tune generative models for talking-head synthesis, audio-driven facial animation, and full-body avatar video, using approaches such as diffusion models, DiT, 3D Gaussian Splatting, GAN-based, and transformer-based video generators.
• Design end-to-end data pipelines for large-scale video, audio, and multimodal datasets, including collection, cleaning, labeling, alignment, and augmentation.
• Optimize models for real-time serving with sub-200ms end-to-end latency through methods like distillation, quantization, pruning, caching, streaming inference, and custom CUDA/Triton kernels when needed.
• Build and maintain training, evaluation, and deployment infrastructure on GPU clusters using PyTorch, DeepSpeed, FSDP, Ray, and Kubernetes.
• Define and track quality metrics such as lip-sync accuracy, identity preservation, expression naturalness, latency, and throughput, then use those measurements to drive iteration.
• Partner with backend, product, and research teams to ship avatar features and incorporate user feedback.
• Stay current with research in generative video, multimodal AI, and neural rendering, and bring proven techniques into the production stack.

What you bring

• 3+ years of hands-on ML engineering or strong research experience with production-quality code, including a record of shipping deep learning models.
• Deep expertise in PyTorch and modern deep learning workflows, with the ability to read, reproduce, and extend research papers.
• Strong background in one or more areas such as diffusion models, video generation, generative AI, computer vision, multimodal (audio+vision) AI, speech synthesis, or neural rendering.
• Solid Python engineering experience, including distributed training on multi-GPU and multi-node setups.
• Proven real-time inference optimization experience with tools such as TensorRT, ONNX, Triton Inference Server, CUDA, mixed precision, and streaming pipelines.
• Comfort working in ambiguous, fast-changing environments, with proactive, ownership-driven execution.
• A startup mentality and eagerness to advance the capabilities of interactive avatars.

Technologies

• PyTorch, DeepSpeed, FSDP, Ray, Kubernetes, CUDA, Triton, Triton Inference Server, TensorRT, ONNX, Python

Benefits

• Competitive salary, equity, and benefits; access to substantial GPU compute.

Nice to have

• Experience related to talking-head, audio-driven animation, lip-sync, or digital human systems, plus familiarity with 3D Gaussian Splatting, NeRF, face reenactment, or avatar synthesis.
• Publications at top venues such as NeurIPS, CVPR, ICCV, SIGGRAPH, ICLR, or ICML, or notable open-source contributions.

Compensation

• Competitive salary, equity, and benefits; access to substantial GPU compute. No range listed.
• Equal Opportunity Employer.

Location: Palo Alto, CA (onsite)

Minimum Experience: 3 years