Applied AI Engineer

About ActAI There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting.

We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our first application is an agent-first mobile communication app.

We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting.

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 C