Senior Machine Learning Engineer
webAI is a sovereign AI platform that lets organizations build, deploy, and operate custom AI on their own infrastructure. It serves enterprise teams across industries such as healthcare, manufacturing, financial services, aviation, public sector, and retail.
Projects
About webAI
webAI provides a full-stack, locally operated AI platform for enterprises seeking private, controllable AI. Its platform includes Navigator for building, training, and deploying custom models; Companion, an on-device AI assistant; Runtime for distributed workload orchestration; webFrame for optimized inference and training; Network for secure local connectivity; and a CLI for programmatic management. The company emphasizes data sovereignty, local deployment, predictable costs, and support for edge devices and private clusters.
Skills
About the Role
You will transform prototype AI models into scalable, efficient, and reliable production systems for secure distributed environments. You will design agentic workflows, build retrieval-augmented generation pipelines, optimize models for cloud, edge, and mobile hardware, and work across multimodal AI domains.
Requirements
- Hold an active United States security clearance
- Have 4+ years of experience in applied AI, machine learning engineering, or production AI systems
- Demonstrate deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers
- Have experience deploying AI models across cloud, edge, and mobile hardware environments
- Demonstrate expertise in model compression and optimization, including quantization, pruning, and distillation
- Have experience building retrieval-augmented generation pipelines and integrating vector databases
- Be familiar with multimodal models and synthetic data generation methods
- Demonstrate algorithmic and problem-solving skills in distributed or constrained compute environments
Responsibilities
- Design, develop, and deploy agentic workflows for multi-step reasoning, tool use, and decision-making
- Productionize AI research prototypes into scalable, deployable systems
- Engineer adaptive machine learning systems using LoRA, PEFT, and on-device inference strategies
- Implement model optimization techniques including quantization, pruning, distillation, and hardware-specific acceleration
- Build and maintain retrieval-augmented generation pipelines with vector database integration
- Work with multimodal AI systems across computer vision, audio, and natural language
- Optimize model execution for distributed and resource-constrained environments
Benefits
- Comprehensive health, dental, and vision benefits package
- 401(k) match for United States-based employees
- $200/month Health & Wellness stipend
- Continuing Education support
- $500/year Function Health subscription for United States-based employees
- Free parking for in-office employees
- Flexible Time Off
- Parental leave for eligible employees
- Supplemental life insurance
