AI Engineer

Embedding; Palo Alto (CA); Sur place; USD 180 000 - 260 000; Plein temps

Résumé du poste

LiveX AI in Palo Alto, CA seeks an AI Engineer to join the Engineering team. You will train and deploy generative models powering talking-head avatars, building end-to-end pipelines from data curation to low-latency inference for live streaming.

The role requires hands-on ML experie nce with PyTorch, diffusion/video models, and multi-GPU training. A fast-paced startup environment values ownership and proactive problem-solving.

Qualifications

• 3+ years of hands-on ML engineering with production-quality code and a track record of shipping deep learning models.
• Strong expertise in PyTorch and modern DL workflows; ability to read, reproduce, and extend research papers.
• Background in diffusion models, video generation, generative AI, computer vision, or multimodal AI (audio+vision).
• Solid Python engineering; experience with distributed training on multi-GPU / multi-node setups.

Responsabilités

• Train and fine-tune generative models for talking-head synthesis and avatar video generation.
• Design data pipelines for large-scale video, audio, and multimodal datasets.
• Optimize models for realtime serving with sub-200ms end-to-end latency using CUDA/Triton techniques.
• Build and maintain training, evaluation, and deployment infra on GPU clusters (PyTorch, DeepSpeed, FSDP, Ray, Kubernetes).
• Define and track quality metrics and drive measurable gains.
• Collaborate with backend, product, and research teams to ship avatar features and iterate on feedback.
• Stay current with research in generative video, multimodal AI, and neural rendering.

Connaissances

PyTorch expertise

Python programming

Distributed training

Realtime inference optimization

CUDA/Triton optimization

Multi-GPU / multi-node

Research-to-production mindset

Outils

TensorRT

ONNX

Triton Inference Server

CUDA

DeepSpeed

Description du poste

LiveX AI · AI Engineer (Machine Learning Engineer) Palo Alto, CA · Full-time, on-site · Department: Engineering Source: https://livex.ai/careers/ai-engineer (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.