Applied AI Engineer

Responsibilities

• ● 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.
• ● 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.
• ● 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
• ● PyTorch / JAX
• ● LLMs (OpenAI-style APIs, LLaMA, Qwen, etc.)
• ● Inference / serving (e.g. vLLM)
• ● 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 product)
• ● Strong problem-solving skills in ambiguous, fast-moving environments