Machine Learning Engineer

Limassol, Tbilisi, Paphos

We develop and implement machine learning and AI solutions across a range of products: AI assistants, customer support chatbots, intelligent data processing, generative AI features, recommender systems, spam detection, search and other ML-powered modules.

Our goal is to build reliable ML and AI systems that solve real product problems — from experimentation and prototyping to production integration and continuous improvement.

Responsibilities

• Designing and implementing ML and AI modules for various products, from experimentation and prototyping to production integration

• Building solutions based on LLMs and other ML/NLP approaches for data processing, generation, search, assistants, bots, agents and automation

• Choosing and evaluating appropriate approaches — including external AI providers, open-source or self-hosted models, as well as traditional ML/NLP methods

• Contributing to the architecture of ML solutions, shaping technical approaches and engineering standards

• Preparing and processing data, training models, running A/B tests, and analyzing results

• Monitoring and improving model performance, interpreting model behavior and key metrics

• Evaluating AI-system quality, analyzing failure cases and improving models, prompts, data and system architecture

• Collaborating with product managers, engineers, and analysts to clarify requirements, integrate solutions, and evaluate their impact

• Working with MLOps infrastructure: CI/CD, monitoring, logging, containerization

What makes you the perfect fit

• 3+ years of experience in ML engineering and building production-ready ML systems

• Strong practical expertise in NLP, LLMs, AI assistants and related AI/ML areas

• Experience with both modern LLM-based systems and traditional ML/NLP approaches such as classification, ranking, retrieval, semantic similarity and information extraction

• Strong track record of delivering end-to-end ML solutions — from idea and data to production and support

• Proficient Python/Go skills and experience with production-grade development

• Experience evaluating ML/AI solutions and understanding their quality, reliability, latency and cost trade-offs

• Solid knowledge of A/B testing and result interpretation

• Experience in architectural decision-making and a drive to improve engineering practices

• Familiarity with tools like Docker, Kubernetes, CI/CD systems, monitoring (e.g. Prometheus, Grafana), and logging

Will be a plus

• Product-oriented mindset and understanding of business metrics

• Experience building real-time and high-load ML systems

• Experience with open-source or self-hosted models

• Familiarity with modern MLOps tools (e.g. MLflow, Airflow, Kubeflow)

• Experience evaluating the UX of AI-driven interactions

What we offer you

• Flexible working hours and a hybrid work format

• Well-equipped offices for focused and collaborative work

• A global, distributed team of 500+ professionals

• Learning, mentorship, and long-term career growth

• Relocation support and private health insurance

• Performance-based bonuses

• TradingView Premium access

• Regular team events and company-wide meetups