Machine Learning Engineer
Summary
Build and improve production-grade machine learning systems for an AI assistant that handles conversations, planning, and task automation using Python, PyTorch/JAX, and GPU-based inference.
About Us
More than 5 billion people use everyday applications like email, notes, and task managers. Most of these apps do not use AI in a smart way. We are building an AI assistant that helps people with conversations, daily tasks, planning, and work. It is easy to use and requires very little input from users.
Our product is designed to handle long tasks, remember useful information, and help users complete real work. It can solve problems step by step, connect with external tools, and stay reliable even when AI responses are not always predictable. Our goal is to help users finish daily tasks faster while making the experience simple and enjoyable.
Role
As a Member of Technical Staff – Machine Learning, you will help build the main machine learning systems used in our product. From your first day, you will work on production systems and learn how machine learning performs in real applications, not only in research.
This role is a good fit for engineers who want to improve their skills by building, testing, fixing, and improving machine learning systems used by real users.
Main Responsibilities
Build and improve machine learning components for data processing, model training, evaluation, and inference.
Fine-tune and adapt machine learning models for production systems.
Create tests and evaluation methods to understand model performance.
Help build and maintain data pipelines for real and synthetic datasets.
Find and solve model issues, performance problems, and production incidents.
Deliver improvements step by step based on user feedback.
Work closely with senior machine learning engineers and product teams.
Build solutions that meet production requirements for speed, cost, reliability, and safety.
Technologies
Python
PyTorch / JAX
Production machine learning systems running on GPUs
Requirements
Good knowledge of machine learning and modern neural network architectures.
Some experience training, fine-tuning, or deploying machine learning models.
Ability to write clean, production-ready code and learn new technologies quickly.
Curious, willing to learn, and open to feedback.
Comfortable working on unclear problems with support from experienced team members.
Interested in delivering solutions quickly and improving them over time.
Expected Results
Machine learning models achieve the required accuracy, speed, and reliability in production.
Production problems are detected and solved quickly with clear root-cause analysis.
Data pipelines, training systems, and inference services are reliable and easy to maintain.
Work effectively with engineering, research, and product teams to deliver AI-powered features.
Improve models and systems continuously using real user feedback and measurable results.
How We Work
We believe the best products are created by small teams with excellent skills. We work closely together, make decisions as a team, and move quickly while maintaining high quality. We encourage everyone to work independently, stay organized, and make good decisions. Our goal is to build an AI product that brings real value to users every day.
Interview Process
If your experience matches our requirements, we will invite you to 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 build AI products that improve everyday life for billions of users.