Our client is looking for a Member of Technical Staff, Machine Learning to help build core machine learning components for a proactive AI assistant. The successful candidate will work on real production systems from day one, gaining hands-on experience with how large-scale machine learning behaves outside research environments. This role is suited to an engineer who wants to develop strong systems judgment by shipping, debugging, evaluating, and improving real-world ML systems. They will work closely with experienced machine learning engineers and product teams while gradually taking greater ownership of technical initiatives.
Responsibilities
Build and improve machine learning components across data preparation, training, evaluation, and inference
Fine-tune and adapt models as part of larger production systems
Implement evaluation and testing frameworks to better understand model behaviour and performance
Help build and maintain pipelines for real-world and synthetic training data
Investigate model failures, performance issues, and production incidents
Ship improvements iteratively and use real user feedback to guide further development
Work closely with senior machine learning engineers, product teams, and other technical stakeholders
Contribute to systems operating under production constraints, including latency, cost, reliability, scalability, and safety
Improve the quality and maintainability of ML systems through testing, monitoring, and continuous iteration
Requirements
Strong foundations in machine learning and modern neural network architectures
Hands-on experience training, fine-tuning, evaluating, or deploying machine learning models
Strong Python programming skills; experience with PyTorch and/or JAX
Familiarity with production machine learning systems running on GPUs
Ability to write clean, reliable, and production-quality code
Understanding of the machine learning lifecycle, including data preparation, training, evaluation, inference, and deployment
Ability to learn new tools and technologies quickly
Ability to work through ambiguous technical problems with guidance
Willingness to take increasing ownership as experience and confidence grow
WHAT THEY OFFER
Cash and equity compensation
Remote-first setup with flexible hours as part of a distributed, global team
Generous paid time off
Company laptop provided
A quick hiring process – 3, occasionally 4, interviews, with fast decisions afterwards
ABOUT THE COMPANY They’re an early-stage AI company building a proactive assistant aimed at the 5+ billion people currently stuck using non-AI-native tools for everyday things – email, notes, tasks. The focus is squarely on reliability: long-running workflows, persistent context, and tasks that actually get done, even though the underlying models aren’t fully deterministic. Stage: Early-stage AI startup Focus: Proactive AI assistant for everyday productivity Work mode: Remote-first, distributed team