Member of Technical Staff — Machine Learning

Nasze wymagania:
Strong foundations in Machine Learning and modern neural network architectures.
Some hands-on experience training, fine-tuning or deploying Machine Learning models.
Ability to write production-quality code and learn new tools quickly.
Curiosity, openness to feedback and a strong willingness to learn from production systems.
Ability to work through ambiguity with guidance and gradually take ownership of increasingly complex problems.
A delivery-oriented mindset focused on shipping, measuring, iterating and continuously improving systems.

O projekcie:
About the product:
Our client is developing an AI-native assistant designed to support everyday communication, organization, errands and complex workflows with minimal user input.
The product must reliably manage long-running processes, retain context, interact with external tools and complete real-world tasks despite the non-deterministic nature of modern AI models. The company’s objective is to make everyday activities significantly faster and easier for users.
About the role:
As a Member of Technical Staff specializing in Machine Learning, you will build and improve core ML components used in a production AI product.
You will work with real production systems from the beginning, developing an understanding of how large-scale Machine Learning operates outside controlled research environments.
This position is intended for an engineer who wants to strengthen their systems judgment by shipping, debugging and continuously improving real-world ML solutions.
What success looks like?
• Production Machine Learning models consistently meet accuracy, latency and reliability expectations.
• Production issues are detected quickly, diagnosed effectively and resolved at the root-cause level.
• Data pipelines, training workflows and inference systems are robust, reproducible and maintainable.
• ML-powered functionality is delivered through effective collaboration with engineering, product and research teams.
• Improvements to models and systems are driven by real-world signals, measurable outcomes and user feedback.
Technology stack:
• Python
• PyTorch / JAX
• GPU-based production Machine Learning systems

Zakres obowiązków:
Build and improve Machine Learning components across data, training, evaluation and inference.
Fine-tune and adapt models as part of larger production systems.
Implement evaluation and testing methods to understand and measure model behavior.
Help build and maintain pipelines for real-world and synthetic data.
Diagnose model failures, performance problems and production incidents.
Deliver improvements iteratively and learn from real user feedback.
Work closely with senior Machine Learning engineers, product teams and other technical specialists.
Operate under real production constraints, including latency, cost, reliability and safety.