We are looking for an experienced and proactive senior-level ML Research Engineer to join our R&D team. In this role, you will be given a chance to work on translating interesting domain-specific challenges into scalable, production-ready solutions.

Key Responsibilities: 

• Translate high-level business problems and domain-specific challenges into tangible technical specifications and innovative ML-powered solutions
• Research and integrate state-of-the-art AI methodologies (e.g., RAG systems, intelligent agents, LLM orchestration)·         Design, develop, test, and evaluate ML models 
• Collect and preprocess large datasets, ensuring data quality and transforming raw data into usable formats for model training
• Lead the team through complex technical challenges, set best practices, and mentor junior engineers to foster a culture of technical excellence and continuous learning
• Actively contribute to team discussions on models, data strategy, and academic literature, helping to drive the team’s collective knowledge forward
• Participate in defining solutions and creating solution architecture.
• Actively participate in cross-functional discussions and strategic decisions related to AI directions and product roadmaps·         Implement production-ready code
• Ensure code quality, scalability, and reliability

Required Qualifications: 

• 5+ years of professional experience·        
• Degree in Computer Science, Mathematics, Physics, or a related field
• Strong foundation in mathematics, algorithms, and data structures
• Experience in reinforcement learning
• Expert-level Python proficiency and hands-on experience with ML libraries (e.g., PyTorch, TensorFlow)
• Proven track record of reading and implementing academic research
• Sharp analytical and problem-solving skills, including translating business requirements into robust technical solutionsPreferred

Qualifications:

• Experience with modern AI systems: RAG architectures, intelligent agents, LLM orchestration
• Experience building and maintaining ML-driven systems in a production environment
• Practical knowledge of MLOps tooling and best practices

Working time:  

• Three remote days per week (hybrid model)     
• Flexible start time: any time from 07:30 to 10:00

About Department and Projects

Our R&D department is where we transform the latest academic research into robust, industry-ready applicable solutions.  Our work spans the entire machine learning lifecycle, from data ingestion and analysis, through model design and evaluation, to reliable production deployment. As a Senior Machine Learning Research Engineer, you will have the opportunity to contribute to and lead a diverse portfolio of impactful projects, including:

• Stem Separation

A proprietary deep-learning architecture used for isolating individual audio sources (vocals, instruments) from mixed recordings.

• Hawkadoc

An intelligent document-parsing platform that includes microservices development, layout and entity-recognition models, and orchestration of components into a flexible document-processing pipeline.

• Synthetic Data

As part of a multinational research consortium, we devised a methodology for generating tabular approximations of peptides and clinical datasets that preserve both privacy and statistical representativeness. We are developing a domain-agnostic framework for synthetic data generation across various industries.

• Data Intelligence

A next-generation platform for conversational BI that enables ad-hoc reporting on structured data across multiple federated databases. You will leverage AI for automated metadata onboarding, apply advanced LLM techniques for conversational intent and interaction, and develop systems for result explanation and data lineage.