About the project

• We’re looking for an experienced AI/ML Engineer to join a team focused on building cutting-edge solutions using Generative AI, Graph Neural Networks (GNN), and scalable data pipelines on Google Cloud Platform. In this role, you'll have the opportunity to design and implement advanced machine learning models (LLMs, diffusion models), work with real-world data at scale, and deploy solutions in production using modern MLOps tools and practices.

Your responsibilities

• Design, implement, and optimize Graph Neural Network (GNN) architectures.
• Build and maintain embedding generation pipelines using ScaNN and related tools.
• Develop and train advanced machine learning models, including LLMs and diffusion models.
• Work with large-scale datasets and build robust data pipelines using GCP services (BigQuery, Dataflow).
• Leverage Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store) for end-to-end ML workflows.
• Apply MLOps best practices to deploy, monitor, and manage models in production environments.
• Collaborate with cross-functional teams including data engineering, research, and software engineering.

Our requirements

• Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field - or equivalent practical experience.
• 5+ years of experience in AI/ML engineering, including at least 2+ years working with Generative AI (e.g., LLMs, diffusion models).
• Hands-on experience with GCP AI/ML services, particularly Vertex AI components.
• Proficiency in Python and strong knowledge of ML frameworks such as TensorFlow, PyTorch, JAX, and Hugging Face Transformers.
• Experience with data engineering and building scalable AI/ML data pipelines on GCP.
• Solid foundation in machine learning algorithms, deep learning, neural networks, and NLP.
• Familiarity with MLOps tools and principles for model lifecycle management.
• Strong analytical and problem-solving skills, with a drive for building impactful AI systems.
• Fluent English (C1) and ability to work effectively in a distributed, international team.
• Certification as a PMLE (Professional Machine Learning Engineer) or equivalent qualification is required.

Technologies we use

This is how we work on a project

• Continuous Deployment

• Continuous Integration

• DevOps

What we offer

• Fully remote work with flexible working hours - EMEA Timezone.

• Long-term collaboration on B2B contract.

• Opportunity to work on complex cloud projects for international clients.

• Professional growth in a highly skilled and supportive team.

• Collaborative and open working culture.