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WebAI

Modular secure edge AI platform

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • Active United States security clearance.
  • At least 4 years of experience in applied artificial intelligence, machine learning engineering, or production artificial intelligence systems.
  • Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers.
  • Proven experience deploying artificial intelligence models across cloud, edge, and mobile hardware environments.
  • Expertise in model compression and optimization, including quantization, pruning, and distillation.
  • Experience building Retrieval Augmented Generation pipelines and integrating vector databases such as Quadrant, ChromaDB, FAISS, Milvus, or Pinecone.
  • Familiarity with multimodal models and synthetic data generation methods.
  • Strong algorithmic and problem-solving skills, especially in distributed or compute-constrained environments.

Responsibilities

  • Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems.
  • Productionize artificial intelligence models from research prototypes into scalable, deployable systems used in real-world applications.
  • Engineer adaptive machine-learning systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.
  • Implement model-optimization techniques such as quantization, pruning, distillation, and hardware-specific acceleration.
  • Build and maintain Retrieval Augmented Generation pipelines, including vector-database integration for contextual retrieval.
  • Work with multimodal artificial-intelligence systems across computer vision, audio, and natural-language domains.
  • Optimize model execution for distributed and resource-constrained environments, ensuring reliability under variable connectivity conditions.

Desired Qualifications

  • Experience with edge artificial intelligence, federated learning, or offline inference systems.
  • Understanding of artificial-intelligence governance and compliance frameworks relevant to public-sector deployments.
  • Experience integrating models into large-scale distributed systems or microservice architectures.
  • Strong understanding of GPU computing, CUDA, and performance profiling.

About the Company

WebAI

Modular secure edge AI platform

WebAI provides a modular, secure Deep Learning Platform designed for research, distributed deployment, and enterprise AI, optimized for edge computing with limited connectivity. Clients collect, train, and deploy neural networks autonomously through a subscription-based suite of AI tools, with optional custom model development and deployment support. It differentiates itself with edge-friendly operation, low data requirements, robust security, and a modular architecture that easily integrates with existing systems. Its goal is to make advanced AI accessible to a broad audience while delivering reliable, enterprise-grade solutions for industries like healthcare, finance, and manufacturing.

Company size
51-200
Company stage
Series A
Total funding
$77M
Headquarters
Austin, TX
Founded
2020

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