Applied AI Engineer
⚲ Warszawa
Do uzgodnienia
Wymagania
- Python
- PyTorch
- JAX
Opis stanowiska
Nasze wymagania:
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.
Mile widziane:
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.
O projekcie:
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.
Zakres obowiązków:
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.
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.
Mile widziane:
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.
O projekcie:
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.
Zakres obowiązków:
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.
🔍 Dekoder Ogłoszenia
🟡
Ability to write clean, production-quality code.
Oczekuje się, że będziesz pisać kod, który jest nie tylko funkcjonalny, ale także dobrze udokumentowany, testowalny i łatwy w utrzymaniu przez innych.
🟡
Comfortable working across models, infrastructure, and product.
Będziesz musiał rozumieć i pracować z różnymi aspektami projektu, od samych modeli AI, przez infrastrukturę, na której działają, po końcowe doświadczenie użytkownika.
🔴
Strong problem-solving skills with a bias toward shipping and iteration.
Oczekuje się, że będziesz aktywnie szukać rozwiązań problemów i priorytetowo traktować szybkie wdrażanie rozwiązań, nawet jeśli nie są one idealne od razu.
🟡
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.
Będziesz odpowiedzialny za cały cykl życia funkcji AI, co może oznaczać dużą odpowiedzialność i szeroki zakres zadań.
🔴
Collaborate closely with Product and Engineering to solve ambiguous problems.
Będziesz musiał pracować z innymi zespołami nad problemami, które nie są jasno zdefiniowane, co wymaga dobrej komunikacji i umiejętności radzenia sobie z niepewnością.