Senior Machine Learning Engineer

Nasze wymagania:
Proven experience building and shipping Machine Learning systems used by real users.
Strong understanding of how modern Machine Learning models behave—and fail—in production environments.
Ability to write high-quality production code and think in complete systems rather than isolated scripts.
Strong ownership and the ability to work independently from an ambiguous problem through production delivery.
Experience working across data, model training, evaluation and inference.
Ability to communicate clearly, learn quickly and improve systems through continuous iteration.
Sound technical judgment when balancing model quality, latency, cost, reliability and safety.
Ability to mentor peers and raise the technical standard of a Machine Learning team.

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 Senior Machine Learning Engineer operating at Senior Member of Technical Staff level, you will independently own critical ML subsystems running in production.
You will take ambiguous technical problems, design practical solutions and deliver systems that operate reliably at scale.
This is a hands-on, high-impact individual contributor role focused on technical depth, production ownership and measurable product outcomes.
What success looks like?
• Production ML models and systems consistently meet accuracy, latency, reliability and efficiency expectations.
• Complex production problems are monitored, diagnosed and resolved with minimal disruption.
• Training, inference and data pipelines remain robust, scalable and maintainable over time.
• ML systems demonstrate measurable improvement based on real-world signals and user feedback.
• Other engineers receive effective mentorship and technical guidance.
• ML capabilities integrate seamlessly into the wider product and support defined business objectives.
Technology stack:
• Python
• PyTorch / JAX
• GPU-based training and inference systems

Zakres obowiązków:
Build core Machine Learning systems powering a proactive, long-horizon AI product.
Own work end-to-end across data preparation, training, evaluation, inference and continuous iteration.
Transform research concepts into reliable systems operating in production.
Diagnose model failures and system-level issues using real production signals.
Work iteratively: ship solutions, measure outcomes, refine them and repeat.
Collaborate closely with research, product and engineering teams to deliver measurable user impact.
Mentor other Machine Learning engineers and review their work through technical judgment and practical example.
Operate under real production constraints, including latency, cost, reliability and safety.