Machine Learning Engineer
⚲ Warszawa
5 000 - 9 000 USD brutto (UoP)
Wymagania
- Machine Learning
- Python
Opis stanowiska
Machine Learning Engineer
💰 Salary: 5000-9000$ per month (depending on experience)
🕦 Full-time
☑️ CoE
🌴Remote from Warsaw
We are looking for a Machine Learning Engineer for a global leader in unified marketing measurement and optimization, recognized by leading industry analysts. The role sits within a NextGen investment initiative, focused on expanding AI/ML capabilities through predictive analytics, generative AI, and agentic systems.
Requirements
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-Learn, XGBoost, etc.)
• Experience with data pipelines and deploying ML systems in cloud environments (AWS, SageMaker, Docker, Kubernetes)
• Hands-on production experience with LLMs and generative AI services (AWS Bedrock, Anthropic Claude, OpenAI, or comparable)
• Strong foundations in algorithms, data structures, and software engineering
• Attention to detail with a focus on quality control and versioning
Nice to Have
• Advanced degree (Master's or Ph.D.) in CS, ML, applied mathematics, statistics, or related field
• Experience designing automated evaluation, quality monitoring, or self-correction systems for AI/ML applications
• Familiarity with numerical programming and optimization methods
• Background in marketing analytics or communicating technical tradeoffs to non-technical stakeholders
Key Responsibilities
• Design, develop, and test end-to-end machine learning systems
• Implement machine learning and statistical algorithms
• Bridge the gap between data scientists and software engineers — translating analytical specs into production-ready applications
• Build prototypes and MVPs from minimal proofs of concept
• Apply generative AI and agentic approaches to synthetic data generation, model hypothesis development, and automated quality review
💰 Salary: 5000-9000$ per month (depending on experience)
🕦 Full-time
☑️ CoE
🌴Remote from Warsaw
We are looking for a Machine Learning Engineer for a global leader in unified marketing measurement and optimization, recognized by leading industry analysts. The role sits within a NextGen investment initiative, focused on expanding AI/ML capabilities through predictive analytics, generative AI, and agentic systems.
Requirements
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-Learn, XGBoost, etc.)
• Experience with data pipelines and deploying ML systems in cloud environments (AWS, SageMaker, Docker, Kubernetes)
• Hands-on production experience with LLMs and generative AI services (AWS Bedrock, Anthropic Claude, OpenAI, or comparable)
• Strong foundations in algorithms, data structures, and software engineering
• Attention to detail with a focus on quality control and versioning
Nice to Have
• Advanced degree (Master's or Ph.D.) in CS, ML, applied mathematics, statistics, or related field
• Experience designing automated evaluation, quality monitoring, or self-correction systems for AI/ML applications
• Familiarity with numerical programming and optimization methods
• Background in marketing analytics or communicating technical tradeoffs to non-technical stakeholders
Key Responsibilities
• Design, develop, and test end-to-end machine learning systems
• Implement machine learning and statistical algorithms
• Bridge the gap between data scientists and software engineers — translating analytical specs into production-ready applications
• Build prototypes and MVPs from minimal proofs of concept
• Apply generative AI and agentic approaches to synthetic data generation, model hypothesis development, and automated quality review
🔍 Dekoder Ogłoszenia
🔴
NextGen investment initiative, focused on expanding AI/ML capabilities through predictive analytics, generative AI, and agentic systems.
Projekt jest nowy i eksperymentalny, co może oznaczać niepewność co do kierunku rozwoju i stabilności technologii.
🔴
Bridge the gap betwee
Fragment jest urwany, co sugeruje niedokończone lub pośpiesznie przygotowane ogłoszenie, potencjalnie wskazujące na brak dbałości o szczegóły.
🟡
global leader in unified marketing measurement and optimization, recognized by leading industry analysts.
Firma może być dobrze znana w swojej branży, ale niekoniecznie oznacza to innowacyjność lub najlepsze praktyki w dziedzinie ML.
🔴
depending on experience
Zakres wynagrodzenia jest szeroki, co może oznaczać, że niższe widełki są dla kandydatów z mniejszym doświadczeniem, a wyższe są trudne do osiągnięcia.
🟡
Attention to detail with a focus on quality control and versioning
Wymaganie to może być standardem, ale w kontekście ML i potencjalnie eksperymentalnych projektów, może oznaczać dużą odpowiedzialność za utrzymanie stabilności i jakości systemów.