Applied AI Engineer
Core
Building a proactive AI smart assistant for everyday users, focusing on high-reliability long-running workflows, persistent context, and real-world task completion.
Role type
Applied AI Engineer (IC)
Builds
AI features end-to-end (model → system → user experience) for everyday users
Domain
Consumer AI / LLMs / Systems Engineering
Deliverable
production ML models
Required skills
Machine learning, neural network architectures, model training and fine-tuning, production code, system design, prompt engineering, agent workflow design, debugging, latency optimization, evaluation framework development
Preferred skills
Experience with multi-step reasoning, non-deterministic model behavior handling, ambiguous problem solving
Technologies
Python, PyTorch, JAX, LLMs (OpenAI-style APIs, LLaMA, Qwen), vLLM, Vector DB
Responsibilities
Design and iterate on prompts, tools, memory, and agent workflows; Turn raw model outputs into structured, reliable, and predictable behaviors; Debug issues across the full stack (model, orchestration, infra, UX); Optimize for latency, cost, and production reliability; Develop lightweight evaluation frameworks to measure real-world performance
Seniority
Mid-Senior, hands-on IC