Member of Technical Staff Machine Learning

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