Applied AI Engineer
⚲ Warszawa
Do uzgodnienia
Wymagania
- Python
- PyTorch
- JAX
- LLM
Opis stanowiska
As an Applied AI Engineer, you'll turn AI capabilities into real product experiences. You'll own features end-to-end: from shaping model behavior and designing agent workflows to building the systems that make them reliable in production.
Working at the intersection of machine learning, systems, and product, you'll help build AI that users can trust every day.
Responsibilities
• Build and ship AI features from model to user experience.
• Design and improve prompts, tools, memory, and agent workflows.
• Turn model outputs into reliable, production-ready behavior.
• Debug issues across models, orchestration, infrastructure, and UX.
• Optimize AI systems for latency, reliability, and cost.
• Build lightweight evaluation frameworks to measure real-world performance.
• Collaborate closely with Product and Engineering to solve ambiguous problems.
Requirements
• Strong foundation in machine learning and modern neural networks.
• Experience training, fine-tuning, or deploying ML models.
• Strong Python skills and experience with PyTorch and/or JAX.
• Experience working with modern LLMs.
• Ability to write clean, production-quality code.
• Comfortable working across models, infrastructure, and product.
• Strong problem-solving skills with a bias toward shipping and iteration.
Nice to Have
• Experience with LLM serving (e.g. vLLM).
• Experience building AI agents, RAG systems, or tool-calling workflows.
• Experience with vector databases and production AI systems.
Why Join Us?
We believe the best products are built by small, world-class teams. We move fast, value ownership, and balance rapid execution with high engineering standards.
You'll help define how AI products behave in the real world while building an assistant that has the potential to improve how billions of people work every day.
Working at the intersection of machine learning, systems, and product, you'll help build AI that users can trust every day.
Responsibilities
• Build and ship AI features from model to user experience.
• Design and improve prompts, tools, memory, and agent workflows.
• Turn model outputs into reliable, production-ready behavior.
• Debug issues across models, orchestration, infrastructure, and UX.
• Optimize AI systems for latency, reliability, and cost.
• Build lightweight evaluation frameworks to measure real-world performance.
• Collaborate closely with Product and Engineering to solve ambiguous problems.
Requirements
• Strong foundation in machine learning and modern neural networks.
• Experience training, fine-tuning, or deploying ML models.
• Strong Python skills and experience with PyTorch and/or JAX.
• Experience working with modern LLMs.
• Ability to write clean, production-quality code.
• Comfortable working across models, infrastructure, and product.
• Strong problem-solving skills with a bias toward shipping and iteration.
Nice to Have
• Experience with LLM serving (e.g. vLLM).
• Experience building AI agents, RAG systems, or tool-calling workflows.
• Experience with vector databases and production AI systems.
Why Join Us?
We believe the best products are built by small, world-class teams. We move fast, value ownership, and balance rapid execution with high engineering standards.
You'll help define how AI products behave in the real world while building an assistant that has the potential to improve how billions of people work every day.
🔍 Dekoder Ogłoszenia
🔴
own features end-to-end
Będziesz odpowiedzialny za cały cykl życia funkcji, od koncepcji po wdrożenie i utrzymanie, co może oznaczać dużą odpowiedzialność i potencjalnie długie godziny pracy.
🔴
shaping model behavior
Może oznaczać zarówno zaawansowane dostrajanie modeli, jak i bardziej powierzchowne manipulowanie promptami, w zależności od faktycznych potrzeb projektu.
🔴
designing agent workflows
Może wymagać tworzenia skomplikowanych sekwencji działań dla agentów AI, co jest bardziej złożone niż proste integracje.
🔴
solve ambiguous problems
Oznacza, że będziesz musiał radzić sobie z problemami, które nie mają jasno określonych rozwiązań ani wymagań, co wymaga dużej samodzielności i kreatywności.
🔴
bias toward shipping and iteration
Podkreśla nacisk na szybkie dostarczanie działających rozwiązań i ciągłe ich ulepszanie, co może oznaczać pracę w szybkim tempie i częste zmiany.