Job description

LiveX AI · AI Engineer (Machine Learning Engineer) Palo Alto, CA · Full-time, on-site · Department: Engineering Source: livex.ai (posted May 27, 2026) ABOUT THE ROLE LiveX AI is building realtime, interactive AI avatars: digital humans that see, listen, and respond with natural speech and expressive motion. This engineer trains, fine-tunes, and serves the generative models behind these avatars across the full model lifecycle, from data curation and training diffusion, video, and multimodal models to low-latency inference for live streaming. RESPONSIBILITIES - Train and fine-tune generative models for talking-head synthesis, audio-driven facial animation, and full-body avatar video (diffusion models, DiT, 3D Gaussian Splatting, GAN-based, transformer-based video generators). - Design data pipelines for large-scale video, audio, and multimodal datasets: collection, cleaning, labeling, alignment, augmentation. - Optimize models for realtime serving with sub-200ms end-to-end latency: distillation, quantization, pruning, caching, streaming inference, custom CUDA/Triton kernels where needed. - Build and maintain training, evaluation, and deployment infrastructure on GPU clusters (PyTorch, DeepSpeed, FSDP, Ray, Kubernetes). - Define and track quality metrics (lip-sync accuracy, identity preservation, expression naturalness, latency, throughput) and drive measurable gains. - Work with backend, product, and research teams to ship avatar features and iterate on user feedback. - Keep up with research in generative video, multimodal AI, and neural rendering; bring useful techniques into the stack. QUALIFICATIONS - 3+ years of hands-on ML engineering, or strong research experience with production-quality code, with a record of shipping deep learning models. - Deep expertise in PyTorch and modern DL workflows; able to read, reproduce, and extend research papers. - Strong background in one or more of: diffusion models, video generation, generative AI, computer vision, multimodal (audio+vision) AI, speech synthesis, neural rendering. - Solid Python engineering; distributed training on multi-GPU / multi-node setups. - Proven realtime inference optimization: TensorRT, ONNX, Triton Inference Server, CUDA, mixed precision, streaming pipelines. - Comfortable in ambiguous, fast-changing environments; proactive, ownership-driven. - Fast-learning startup mentality; eager to push what interactive avatars can do. NICE-TO-HAVES - Talking-head, audio-driven animation, lip-sync, or digital human systems; 3D Gaussian Splatting, NeRF, face reenactment, avatar synthesis. - Publications at top venues (NeurIPS, CVPR, ICCV, SIGGRAPH, ICLR, ICML) or notable open-source contributions. COMPENSATION Competitive salary, equity, and benefits; access to substantial GPU compute. No range listed. Equal Opportunity Employer. HOW TO APPLY (ORIGINAL POSTING) Email resume and relevant supporting materials to career@livex.ai, subject "Candidate Application - AI Engineer".

Requirements

Must-haves

LiveX AI · AI Engineer (Machine Learning Engineer)
Palo Alto, CA · Full-time, on-site · Department: Engineering
Train and fine-tune generative models for talking-head synthesis, audio-driven facial animation, and full-body avatar video (diffusion models, DiT, 3D Gaussian Splatting, GAN-based, transformer-based video generators).
Design data pipelines for large-scale video, audio, and multimodal datasets: collection, cleaning, labeling, alignment, augmentation.
Optimize models for realtime serving with sub-200ms end-to-end latency: distillation, quantization, pruning, caching, streaming inference, custom CUDA/Triton kernels where needed.
Build and maintain training, evaluation, and deployment infrastructure on GPU clusters (PyTorch, DeepSpeed, FSDP, Ray, Kubernetes).
Define and track quality metrics (lip-sync accuracy, identity preservation, expression naturalness, latency, throughput) and drive measurable gains.
Work with backend, product, and research teams to ship avatar features and iterate on user feedback.
Keep up with research in generative video, multimodal AI, and neural rendering; bring useful techniques into the stack.
3+ years of hands-on ML engineering, or strong research experience with production-quality code, with a record of shipping deep learning models.
Deep expertise in PyTorch and modern DL workflows; able to read, reproduce, and extend research papers.
Strong background in one or more of: diffusion models, video generation, generative AI, computer vision, multimodal (audio+vision) AI, speech synthesis, neural rendering.
Solid Python engineering; distributed training on multi-GPU / multi-node setups.
Proven realtime inference optimization: TensorRT, ONNX, Triton Inference Server, CUDA, mixed precision, streaming pipelines.
Comfortable in ambiguous, fast-changing environments; proactive, ownership-driven.
Fast-learning startup mentality; eager to push what interactive avatars can do.
Email resume and relevant supporting materials to career@livex.ai, subject "Candidate Application - AI Engineer".

Nice-to-haves

Talking-head, audio-driven animation, lip-sync, or digital human systems; 3D Gaussian Splatting, NeRF, face reenactment, avatar synthesis.
Publications at top venues (NeurIPS, CVPR, ICCV, SIGGRAPH, ICLR, ICML) or notable open-source contributions.

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Keywords to mirror

aimachine learningkubernetesmlpython

Platform: ashby
Effort: quick

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