About this role
Description
- 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
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Strong foundations in machine learning and modern neural network architectures
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Hands-on experience training, fine-tuning, evaluating, or deploying machine learning models
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Strong Python programming skills; experience with PyTorch and/or JAX
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Familiarity with production machine learning systems running on GPUs
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Ability to write clean, reliable, and production-quality code
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Understanding of the machine learning lifecycle, including data preparation, training, evaluation, inference, and deployment
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Ability to learn new tools and technologies quickly
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Ability to work through ambiguous technical problems with guidance
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Willingness to take increasing ownership as experience and confidence grow
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WHAT THEY OFFER
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Cash and equity compensation
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Remote-first setup with flexible hours as part of a distributed, global team
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Generous paid time off
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Company laptop provided
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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
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ABOUT COMPENSATION
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