AI & ML Engineer

Remote.Bulgaria
Remote.Georgia
Remote.Poland
Белград
Варна
Варшава
Вроцлав
Днепър
Ереван
Киев
Клуж-Напока
Краков
Ларнака
Лвов
Лодз
Люблин
Одеса
Рига
София
Тбилиси
Харков

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Position overview

We are seeking a highly skilled AI & ML Engineer to join our innovative team. In this role, you will lead the development, optimization, and deployment of advanced machine learning and artificial intelligence models. You will drive state-of-the-art research, build scalable pipelines, and collaborate with cross-functional teams to translate business needs into effective ML solutions.

This position offers the opportunity to work on cutting-edge technologies in a dynamic, fast-paced environment, contributing to impactful projects that power next-generation AI applications.

Responsibilities

Design, implement, and optimize machine learning and AI models, including classification, regression, clustering, and agent tuning.
Experiment with the latest methods, frameworks, and architectures to enhance model performance and efficiency.
Develop robust, scalable ML pipelines for training, validation, and inference.
Deploy ML models into production environments (cloud or on-prem), ensuring high reliability, low latency, and scalability.
Apply MLOps best practices including CI/CD, monitoring, automated retraining, and model registry management.
Partner with data engineering teams to source, clean, and transform large datasets for model training and inference.
Ensure high data quality, perform feature engineering, and support real-time data integration processes.
Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals.
Clearly communicate complex technical results to both technical and non-technical stakeholders.
Provide technical guidance and mentorship to junior ML engineers and data scientists.
Contribute to establishing team best practices, code reviews, and architectural decisions.

Requirements

5+ years of professional experience in machine learning, AI engineering, or related fields.
Master’s degree in Computer Science, Machine Learning, Physics, or related field; PhD preferred.
Proficient in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Strong understanding of algorithms, statistics, probability, and linear algebra.
Hands-on experience with data pipelines and ETL tools (e.g., Spark, AWS Lambda, AWS Glue).
Practical experience with cloud platforms, preferably AWS.
Solid software engineering fundamentals including version control (Git), testing, and design patterns.
Demonstrated success in deploying ML models into production at scale.
Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
Excellent analytical, problem-solving, and communication skills.
Ability to work autonomously and collaboratively within a fast-paced, cross-functional team environment.

Nice to have

Experience with agentic frameworks like LangChain or LangGraph

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