About this role
Senior Machine Learning Engineer is a full-time position based in Sweden, offering an opportunity for an experienced professional to independently own critical machine learning subsystems in production. This role suits a hands-on engineer who excels at transforming ambiguous challenges into reliable, scalable machine learning infrastructure.
Role Overview
The Senior Machine Learning Engineer takes charge of critical machine learning subsystems at ACTAI in Sweden. The position centers on building proactive applications that eliminate complex prompting for everyday tasks like communication, organization, and workflows. Practitioners operate with high autonomy to design, build, and deploy production systems that emphasize reliability and long-running context.
Key Responsibilities
Requirements
Skills and Tools
About the Company
ACTAI builds proactive software applications aimed at billions of users who rely on basic tools like email, notes, tasks, calendars, and workflows without requiring complex prompting. The enterprise focuses on delivering high reliability for long-running workflows, persistent context, and real-world task execution while minimizing hallucinations. Operating as a small, highly talented, and hands-on team, the organization makes collective decisions and moves rapidly to organize daily life so individuals can focus on meaningful tasks.
How to Apply
Interested candidates should apply directly on the official company careers page.
Skills and tech stack
Questions candidates ask
Where is the Senior Machine Learning Engineer position located?
The role is based in Sweden.
What primary technologies are used in this role?
The tech stack includes Python, PyTorch, JAX, and GPU-based training and inference systems.
What is the interview process like?
The interview process consists of three to four total interviews conducted via virtual meetings and/or onsite sessions, evaluated by technical team members.
What are the core objectives of the machine learning products at ACTAI?
The objective is to build proactive applications for long-running workflows, persistent context, and real-world task completion with minimal to no prompting.