ML AI Engineer

Join a team building modern AI solutions. We are looking for an experienced Senior AI/ML Engineer who will be responsible for designing, implementing, and developing production solutions based on Machine Learning and Generative AI. If you have experience in building ML models, automating pipelines, and integrating AI with business systems, this role is for you. Your tasks: * Designing and implementing AI/ML solutions from Proof of Concept to production. * Building and maintaining ML pipelines (data preparation, training, deployment, monitoring). * Integrating AI models with client applications and systems via API and event-driven architecture. * Monitoring model quality and optimizing their performance in production environments. * Collaborating with development, DevOps, and business teams. * Participating in code reviews, making technical decisions, and mentoring less experienced team members. Our requirements: Must have: * Minimum 4 years of experience in AI/ML, Data Engineering, or Software Engineering. * Very good knowledge of Python. * Practical knowledge of: pandas, NumPy, scikit-learn. * Experience in deploying ML models to production environments. * Knowledge of Docker. * Experience in building REST APIs. * Knowledge of SQL (PostgreSQL, MySQL, or similar). * Experience with at least one cloud platform (Azure, AWS, or GCP). Nice to have: * PyTorch or TensorFlow. * LLM, GenAI, and RAG systems. * MLflow, Airflow, Azure ML, SageMaker. * Kubernetes. * Vector databases (FAISS, Pinecone, OpenSearch). * Monitoring and observability (Grafana, Prometheus, OpenTelemetry). * Experience in projects for the public sector. We offer: * Real impact on the architecture and direction of AI solutions development. * Work on projects using Machine Learning, LLMs, and Generative AI. * Flexible working hours and remote work possibility. * Access to a modern technology stack and cloud environments. * Training budget and the possibility to participate in industry conferences. * High autonomy and responsibility for implemented solutions. * Collaboration with an experienced team of technological experts. Technologies: Python • Machine Learning • scikit-learn • pandas • NumPy • Docker • REST API • SQL • Azure/AWS • MLflow • Airflow • LLM • RAG • GenAI • Kubernetes