Senior Machine Learning Engineer
⚲ Warszawa
Do uzgodnienia
Wymagania
- Python
- PyTorch
- JAX
Opis stanowiska
Nasze wymagania:
Strong proficiency in Python.
Hands-on experience with PyTorch and/or JAX.
Experience building GPU-based training and inference systems.
Track record of designing, building, and deploying machine learning systems used by real users.
Ability to write clean, maintainable, production-quality code.
Strong systems-thinking mindset with the ability to solve complex engineering challenges.
Self-driven, highly accountable, and comfortable working independently.
Excellent communication skills and the ability to collaborate across technical disciplines.
Passion for continuous learning and iterative product development.
Mile widziane:
Experience designing large-scale data pipelines.
Experience optimizing ML infrastructure for performance and cost.
Experience with production model monitoring and observability.
Familiarity with distributed training and large-scale AI systems.
O projekcie:
We are looking for a Senior Machine Learning Engineer to design, build, and scale the core machine learning systems powering our AI products. This is a hands-on, high-impact role for someone who enjoys solving ambiguous problems, taking ownership, and delivering production-ready ML solutions that create real value for users.
You will own the full lifecycle of machine learning systems, from data preparation and model training to deployment, monitoring, and continuous improvement. Working closely with Research, Product, and Engineering teams, you will transform cutting-edge ideas into reliable, scalable production systems.
Zakres obowiązków:
Design, develop, and maintain production-grade machine learning systems.
Own the end-to-end ML lifecycle, including data preparation, model training, evaluation, deployment, inference, and iteration.
Build robust and scalable training and inference pipelines.
Translate research ideas into reliable production solutions.
Monitor, debug, and improve ML models using real-world production signals.
Continuously optimize models for accuracy, latency, reliability, efficiency, and cost.
Collaborate closely with Research, Product, and Engineering teams to deliver impactful AI features.
Mentor fellow ML engineers through technical leadership, code reviews, and knowledge sharing.
Ensure ML systems meet production requirements around scalability, performance, safety, and maintainability.
Oferujemy:
Full-time employment
100% remote work
Opportunity to build an AI-native product with global ambitions
Work with state-of-the-art AI technologies and modern backend infrastructure
High ownership and autonomy from day one
Collaboration with an exceptional engineering team passionate about innovation
Fast-paced environment where your ideas have real impact
Opportunity to solve complex engineering challenges at scale
Strong proficiency in Python.
Hands-on experience with PyTorch and/or JAX.
Experience building GPU-based training and inference systems.
Track record of designing, building, and deploying machine learning systems used by real users.
Ability to write clean, maintainable, production-quality code.
Strong systems-thinking mindset with the ability to solve complex engineering challenges.
Self-driven, highly accountable, and comfortable working independently.
Excellent communication skills and the ability to collaborate across technical disciplines.
Passion for continuous learning and iterative product development.
Mile widziane:
Experience designing large-scale data pipelines.
Experience optimizing ML infrastructure for performance and cost.
Experience with production model monitoring and observability.
Familiarity with distributed training and large-scale AI systems.
O projekcie:
We are looking for a Senior Machine Learning Engineer to design, build, and scale the core machine learning systems powering our AI products. This is a hands-on, high-impact role for someone who enjoys solving ambiguous problems, taking ownership, and delivering production-ready ML solutions that create real value for users.
You will own the full lifecycle of machine learning systems, from data preparation and model training to deployment, monitoring, and continuous improvement. Working closely with Research, Product, and Engineering teams, you will transform cutting-edge ideas into reliable, scalable production systems.
Zakres obowiązków:
Design, develop, and maintain production-grade machine learning systems.
Own the end-to-end ML lifecycle, including data preparation, model training, evaluation, deployment, inference, and iteration.
Build robust and scalable training and inference pipelines.
Translate research ideas into reliable production solutions.
Monitor, debug, and improve ML models using real-world production signals.
Continuously optimize models for accuracy, latency, reliability, efficiency, and cost.
Collaborate closely with Research, Product, and Engineering teams to deliver impactful AI features.
Mentor fellow ML engineers through technical leadership, code reviews, and knowledge sharing.
Ensure ML systems meet production requirements around scalability, performance, safety, and maintainability.
Oferujemy:
Full-time employment
100% remote work
Opportunity to build an AI-native product with global ambitions
Work with state-of-the-art AI technologies and modern backend infrastructure
High ownership and autonomy from day one
Collaboration with an exceptional engineering team passionate about innovation
Fast-paced environment where your ideas have real impact
Opportunity to solve complex engineering challenges at scale
🔍 Dekoder Ogłoszenia
🔴
Self-driven, highly accountable, and comfortable working independently.
Oczekuje się, że będziesz pracować bez ciągłego nadzoru i samodzielnie rozwiązywać problemy, co może oznaczać mniejszą pomoc ze strony zespołu.
🟡
Ability to write clean, maintainable, production-quality code.
Oczekuje się, że kod będzie nie tylko działał, ale także będzie łatwy do zrozumienia i modyfikacji przez innych, co może wymagać więcej czasu na refaktoryzację.
🟡
Passion for continuous learning and iterative product development.
Może oznaczać, że będziesz musiał ciągle uczyć się nowych technologii i dostosowywać się do zmieniających się wymagań projektu.
🔴
Track record of designing, building, and deploying machine learning systems used by real users.
Wymaga udokumentowanego doświadczenia w tworzeniu i wdrażaniu systemów ML, które faktycznie są używane, co może być trudne do udowodnienia bez konkretnych projektów.
🔴
You will own the full lifecycle of machine learning systems, from data preparation and model training to deployment, monitoring, and continuous improvement.
Oznacza to szeroki zakres odpowiedzialności, od początkowych etapów po utrzymanie, co może być bardzo wymagające i czasochłonne.