Applied AI Engineer
Summary
Build and deploy AI features for a consumer-facing assistant, integrating LLMs, vector databases, and inference tools into reliable production systems.
About Us
More than 5 billion people use everyday apps such as email, notes, and task managers. Most of these tools do not use AI in a smart way. We want to create an AI assistant that helps people with conversations, daily tasks, planning, and work. The assistant should be easy to use and require very little effort from users.
Our product is built to handle long tasks, remember useful information, and help users complete real work. It can solve problems step by step, connect with different tools, and work reliably even when AI responses are not always predictable. Our goal is to help users save time and make everyday tasks easier.
Role
As an Applied AI Engineer, you will build AI features that people can use in real products. You will work on the whole process, from improving AI models to creating reliable systems that perform well in production.
This role combines machine learning, software engineering, and product development. Your job is to make AI useful in real situations, not only in demonstrations.
Main Responsibilities
Build and deliver AI features from the model to the final user experience.
Design and improve prompts, memory, tools, and AI agent workflows.
Turn AI responses into clear, reliable, and consistent results.
Find and fix problems across the whole system, including models, infrastructure, and user experience.
Improve speed, cost, and reliability of AI services.
Create simple evaluation methods to measure AI performance in real use.
Work closely with product managers and software engineers to solve complex problems.
Technologies
Python
PyTorch / JAX
Large Language Models (LLMs), including OpenAI APIs, LLaMA, and Qwen
Inference tools such as vLLM
Vector databases
Requirements
Good knowledge of machine learning and modern neural networks.
Experience training, fine-tuning, or deploying machine learning models.
Ability to write clean and maintainable production code.
Comfortable working with different parts of AI systems, from models to infrastructure and products.
Strong problem-solving skills in fast-changing environments.
Interest in delivering solutions quickly and improving them over time.
Expected Results
AI models meet performance, speed, and reliability goals in production.
Production problems are found and solved quickly with clear root-cause analysis.
Data pipelines, model training, and inference systems are stable and easy to maintain.
Work effectively with engineering, research, and product teams to deliver AI features.
Improve models and systems based on real user feedback and measurable results.
How We Work
We believe great products are built by small teams with excellent skills. We work together, make decisions as a team, and move quickly while keeping high quality. We expect everyone to stay organized, make good decisions, and work independently. Our goal is to build an AI product that brings real value to users.
Interview Process
If your skills match our needs, we will invite you to take part in 3 or 4 interviews.
Our technical team reviews every application. Interviews are held online or in person.
We keep the hiring process simple and efficient. If you show the skills and attitude we are looking for, we will invite you to join our team. We are looking for people who want to help create AI products that improve everyday life for billions of users.