Data Scientist - AI Engineer
SQUARE ONE RESOURCES sp. z o.o.
⚲ Warszawa
Do uzgodnienia
Wymagania
- Python
- NLP
- HuggingFace Transformers
- AWS
- Amazon SageMaker
- Amazon MWAA
- Amazon Athena
- scikit-learn
- Docker
Opis stanowiska
Nasze wymagania:
Strong Python programming skills, including production-grade development.
Hands-on experience building and deploying end-to-end ML systems.
Practical experience with Machine Learning projects in commercial environments.
Experience developing AI agents or intelligent customer-facing applications.
Strong knowledge of NLP and transformer-based architectures (e.g. HuggingFace).
Experience working with customer feedback analysis and CX prediction models.
Good knowledge of AWS services, especially Amazon SageMaker, Amazon MWAA, and Amazon Athena.
Experience with scikit-learn and other ML frameworks.
Experience with Docker and ML deployment workflows.
Excellent communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.
Mile widziane:
Experience working in cloud-native AI environments.
Knowledge of MLOps best practices.
Experience delivering AI solutions at scale.
O projekcie:
Delivering AI-powered, customer-facing solutions.
Design, develop, and deploy end-to-end machine learning and NLP systems.
Creating impactful AI products by working closely with both technical and business stakeholders.
Zakres obowiązków:
Design, build, and deploy end-to-end Machine Learning solutions, from experimentation to production.
Develop AI agents for customer-facing use cases.
Experiment with various ML techniques to identify the most effective approach for different business problems.
Design and implement NLP solutions, including transformer-based models.
Analyze customer feedback data and build Customer Experience (CX) prediction models.
Collaborate with cross-functional teams to translate business requirements into scalable AI solutions.
Support production deployment and maintenance of ML models using modern MLOps practices.
Strong Python programming skills, including production-grade development.
Hands-on experience building and deploying end-to-end ML systems.
Practical experience with Machine Learning projects in commercial environments.
Experience developing AI agents or intelligent customer-facing applications.
Strong knowledge of NLP and transformer-based architectures (e.g. HuggingFace).
Experience working with customer feedback analysis and CX prediction models.
Good knowledge of AWS services, especially Amazon SageMaker, Amazon MWAA, and Amazon Athena.
Experience with scikit-learn and other ML frameworks.
Experience with Docker and ML deployment workflows.
Excellent communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.
Mile widziane:
Experience working in cloud-native AI environments.
Knowledge of MLOps best practices.
Experience delivering AI solutions at scale.
O projekcie:
Delivering AI-powered, customer-facing solutions.
Design, develop, and deploy end-to-end machine learning and NLP systems.
Creating impactful AI products by working closely with both technical and business stakeholders.
Zakres obowiązków:
Design, build, and deploy end-to-end Machine Learning solutions, from experimentation to production.
Develop AI agents for customer-facing use cases.
Experiment with various ML techniques to identify the most effective approach for different business problems.
Design and implement NLP solutions, including transformer-based models.
Analyze customer feedback data and build Customer Experience (CX) prediction models.
Collaborate with cross-functional teams to translate business requirements into scalable AI solutions.
Support production deployment and maintenance of ML models using modern MLOps practices.
🔍 Dekoder Ogłoszenia
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production-grade development
Oczekuje się, że kod będzie wysokiej jakości, gotowy do wdrożenia na produkcji, a nie tylko prototypowy.
🟡
end-to-end ML systems
Musisz być w stanie samodzielnie przeprowadzić cały cykl życia modelu ML, od danych po wdrożenie i monitorowanie.
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AI agents or intelligent customer-facing applications
Prawdopodobnie będziesz pracować nad rozwiązaniami, które bezpośrednio wchodzą w interakcję z klientami, co może oznaczać potrzebę uwzględnienia aspektów UX i skalowalności.
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customer feedback analysis and CX prediction models
Może to oznaczać pracę z dużą ilością nieustrukturyzowanych danych tekstowych i potrzebę zrozumienia metryk satysfakcji klienta.
🟡
delivering AI solutions at scale
Oczekuje się, że będziesz w stanie wdrażać i zarządzać rozwiązaniami AI, które obsługują dużą liczbę użytkowników lub danych.