Applied AI Engineer

ABOUT A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time. ROLE As an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production. This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real-world usage. FOCUS - Build and ship AI features end-to-end (model → system → user experience) - 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 - Work closely with product and engineering to translate ambiguous problems into working systems TECH STACK - Python - PyTorch / JAX - LLMs (OpenAI-style APIs, LLaMA, Qwen, etc.) - Inference / serving (e.g. vLLM) - Vector DB IDEAL EXPERIENCE - Strong foundation in machine learning and modern neural network architectures. - Hands-on experience with training, fine-tuning, or deploying ML models - Ability to write clean, production-quality code - Comfort working across abstraction layers (model → infra → pro