Senior Machine Learning Engineer
⚲ Warszawa, Kraków
Do uzgodnienia
Wymagania
- Python
Opis stanowiska
The opportunity
An AI company is building systems to help organisations detect and respond to disinformation attacks in real time. The platform combines machine learning, proprietary knowledge of attack and defence techniques, and large-scale, high-throughput data analysis. The founding team brings over forty years of combined experience building data systems used by national security and commercial organisations.
This is a high-ownership, production-focused role - not research. The focus is on real-world systems that are reliable, scalable, and fast.
The role
You'll build and operate production-grade machine learning systems that detect and counter disinformation as it happens. You'll work across the full ML lifecycle - from model development to deployment and monitoring - collaborating with a cross-functional team from software engineering, machine learning, and intelligence backgrounds.
You'll shape both the product and the underlying ML infrastructure.
What you'll work on
• Build and operate production ML systems for real-time disinformation detection
• Own the full ML lifecycle: data, models, deployment, monitoring, and iteration
• Design systems that balance latency vs accuracy, cost vs performance
• Work across relational and non-relational databases and large-scale data processing pipelines
• Contribute to ML infrastructure and help define how the team builds
What we look for
• Production ML experience - you've built and deployed ML systems in production, not just prototypes
• Strong engineering fundamentals - clean, modular, maintainable code that others can build on
• End-to-end ownership - from raw data through to deployed, monitored systems
• Algorithmic versatility - broad exposure across ML approaches; you apply the right method to the problem
• Data systems experience - solid grounding in SQL and NoSQL, streaming and batch processing
• Systems thinking - you design for trade-offs, not just for accuracy
• Infrastructure familiarity - containerisation, CI/CD, production cloud environments
Stack
Python · SQL & NoSQL databases · streaming & batch data processing frameworks · Docker · CI/CD · cloud infrastructure
Benefits
• Competitive salary + early employee equity (share options)
• 25 days holiday + your birthday off
• Private pension contributions
• Remote-first, flexible, outcomes-driven culture
• High ownership from day one
An AI company is building systems to help organisations detect and respond to disinformation attacks in real time. The platform combines machine learning, proprietary knowledge of attack and defence techniques, and large-scale, high-throughput data analysis. The founding team brings over forty years of combined experience building data systems used by national security and commercial organisations.
This is a high-ownership, production-focused role - not research. The focus is on real-world systems that are reliable, scalable, and fast.
The role
You'll build and operate production-grade machine learning systems that detect and counter disinformation as it happens. You'll work across the full ML lifecycle - from model development to deployment and monitoring - collaborating with a cross-functional team from software engineering, machine learning, and intelligence backgrounds.
You'll shape both the product and the underlying ML infrastructure.
What you'll work on
• Build and operate production ML systems for real-time disinformation detection
• Own the full ML lifecycle: data, models, deployment, monitoring, and iteration
• Design systems that balance latency vs accuracy, cost vs performance
• Work across relational and non-relational databases and large-scale data processing pipelines
• Contribute to ML infrastructure and help define how the team builds
What we look for
• Production ML experience - you've built and deployed ML systems in production, not just prototypes
• Strong engineering fundamentals - clean, modular, maintainable code that others can build on
• End-to-end ownership - from raw data through to deployed, monitored systems
• Algorithmic versatility - broad exposure across ML approaches; you apply the right method to the problem
• Data systems experience - solid grounding in SQL and NoSQL, streaming and batch processing
• Systems thinking - you design for trade-offs, not just for accuracy
• Infrastructure familiarity - containerisation, CI/CD, production cloud environments
Stack
Python · SQL & NoSQL databases · streaming & batch data processing frameworks · Docker · CI/CD · cloud infrastructure
Benefits
• Competitive salary + early employee equity (share options)
• 25 days holiday + your birthday off
• Private pension contributions
• Remote-first, flexible, outcomes-driven culture
• High ownership from day one
🔍 Dekoder Ogłoszenia
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