Machine Learning Engineer

• Build and contribute to RAG system components under senior guidance, with growing autonomy
• Write tests and help build evaluation harnesses
• Write production code across AI, backend services, and data pipelines
• Integrate AI components into backend services and RESTful APIs
• Support deployment of containerized systems to AWS using CI/CD
• Contribute to documentation, runbooks, and client handover materials
• Participate in technical discussions and architectural decisions
• Support model evaluation and investigate and improve failure modes
• Take increasing ownership of components and technical decisions

Junior AI/ML Engineer, GenAI, AWS

• Develop and improve real-world computer vision systems, focusing on aerial image recognition
• Build solutions involving object detection, image segmentation, classification, and pattern recognition
• Train, fine-tune, evaluate, and deploy computer vision and machine learning models
• Experiment with modern vision models, foundation models, and multimodal AI technologies
• Research new AI approaches and evaluate their potential product value
• Rapidly build prototypes and validate technical ideas
• Improve model accuracy, reliability, performance, and inference efficiency
• Work with visual data and develop data preparation, training, and evaluation pipelines
• Explore LLMs, embeddings, vision-language models, and emerging AI technologies
• Use AI coding tools and agents to accelerate development, research, debugging, and prototyping
• Identify ways AI can improve the overall product and user experience
• Own technical challenges from initial research through implementation and deployment
• Work directly with the client’s team in an international environment

AI/ML Engineer

• Develop and improve real-world computer vision systems, with a strong focus on aerial image recognition
• Build solutions involving object detection, image segmentation, classification, and pattern recognition
• Train, fine-tune, evaluate, and deploy computer vision and machine learning models
• Experiment with modern vision models, foundation models, and multimodal AI technologies
• Research new AI approaches and evaluate their potential value for the product
• Rapidly build prototypes and validate technical ideas
• Improve model accuracy, reliability, performance, and inference efficiency
• Work with visual data and develop effective data preparation, training, and evaluation pipelines
• Explore the use of LLMs, embeddings, vision-language models, and other emerging AI technologies
• Use AI coding tools and agents to accelerate development, research, debugging, and prototyping
• Identify ways AI can improve the overall product and user experience
• Take ownership of technical challenges from initial research through implementation and deployment
• Work directly with the client’s team on an all-in-one roofing professionals platform

• Develop full-stack machine learning models, including binary classification and regression, for financial-crime detection during transaction processing and client onboarding
• Gather requirements, prototype solutions, and deploy models into production
• Own and evolve the Dynamic Risk Score across all markets, scoring the full client base daily
• Manage transaction rules with ML-driven detection and optimize performance and generated alerts
• Monitor model and rule performance in production
• Develop a champion-challenger framework to keep the best-performing model live
• Participate in infrastructure development for ML operationalization and inter-service interactions
• Serve and infer models of varying complexity

Senior Machine Learning Engineer

• Design and build core machine learning systems for a proactive AI platform
• Own projects end-to-end, including data curation, model training, evaluation, inference, and continuous iteration
• Translate research concepts into robust, reliable production systems
• Use live production signals and data to troubleshoot model anomalies and system bottlenecks
• Deploy systems, analyze real-world performance metrics, refine approaches, and iterate rapidly
• Collaborate with research, engineering, and product teams to connect technical milestones with user value
• Mentor fellow engineers and conduct rigorous code and technical reviews
• Optimize model architectures for latency, computational cost, reliability, and safety at scale

• Own the AI/ML/Vision core of the robotics automation product
• Work closely with the CTO and Co-founder to align ML capabilities with the technical strategy
• Write custom training loops and design and implement neural network architectures
• Manage the end-to-end lifecycle from raw data processing through training, fine-tuning, and edge deployment
• Build AI/ML/Vision components of the MVP
• Define the AI/ML stack and model architecture
• Monitor AI, computer vision, and robotics trends
• Mentor engineers joining the AI/ML function as the team grows
• Translate customer feedback and market needs into robust AI/ML technical requirements
• Contribute to code quality, ownership, rapid iteration, and high execution standards
• Integrate AI capabilities into a commercially viable physical robotics product

Machine Learning Engineer jobs in Poland

Junior AI/ML Engineer, GenAI, AWS

AI/ML Engineer

AI/ML Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer, Robotics & Computer Vision