Machine Learning Engineer
OBI SMART TECHNOLOGIES POLAND SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ
⚲ Katowice
9 000–27 720 zł / mies. (zal. od umowy)
Wymagania
- Python
- SQL
- TensorFlow
- PyTorch
- Pandas
- LLM
- AWS
- Databricks
Opis stanowiska
Nasze wymagania:
Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field
Solid experience building and operating production-grade machine learning pipelines
Strong Python engineering skills, including clean code practices and software engineering best standards
Hands-on experience with Git-based version control and working with CI/CD pipelines as a user
Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP)
Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week
O projekcie:
As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution.
Zakres obowiązków:
Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases
Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring
Ensure robustness, performance and reproducibility of machine learning solutions in production environments
Implement structured and versioned ML workflows supporting reliable model development and operation
Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design
Oferujemy:
Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more.
Language Courses – you'll have access to a multi-language learning platform enabling you to practice you language skills and learn new ones!
Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development.
Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions.
Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field
Solid experience building and operating production-grade machine learning pipelines
Strong Python engineering skills, including clean code practices and software engineering best standards
Hands-on experience with Git-based version control and working with CI/CD pipelines as a user
Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP)
Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week
O projekcie:
As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution.
Zakres obowiązków:
Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases
Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring
Ensure robustness, performance and reproducibility of machine learning solutions in production environments
Implement structured and versioned ML workflows supporting reliable model development and operation
Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design
Oferujemy:
Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more.
Language Courses – you'll have access to a multi-language learning platform enabling you to practice you language skills and learn new ones!
Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development.
Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions.
🔍 Dekoder Ogłoszenia
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Solid experience building and operating production-grade machine learning pipelines
Oczekuje się, że kandydat będzie w stanie samodzielnie wdrażać i utrzymywać kompletne, działające systemy ML w środowisku produkcyjnym, a nie tylko tworzyć prototypy.
🔴
You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution.
Twoja rola będzie mocno techniczna, z minimalnym lub zerowym kontaktem z klientem biznesowym i ograniczonym wpływem na strategię projektu.
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Ensure robustness, performance and reproducibility of machine learning solutions in production environments
Oprócz tworzenia modeli, będziesz odpowiedzialny za zapewnienie ich stabilności, szybkości działania i powtarzalności wyników w rzeczywistych warunkach.
🔴
Implement structured and versioned ML workflows supporting reliable model de
Spodziewaj się konieczności stosowania rygorystycznych praktyk inżynierskich w całym cyklu życia modelu ML, w tym zaawansowanego zarządzania wersjami i przepływami pracy.