Responsibilities

• Develop, deploy, and maintain machine learning models and systems
• Conduct in-depth data analysis, preparation, and processing
• Contribute to the design of ML systems, focusing on data related aspects like annotation and processing
• Follow established security guidelines and identify potential risks
• Collaborate with peers to review and ensure designs are effective, flexible, and reusable
• Solve issues and provide feedback for engineering design and delivery processes
• Ensure that features are deployed according to requirements and operate without unintended side effects
• Create and maintain comprehensive documentation for models and processes
• Monitor and support deployed solutions to ensure they meet performance expectations
• Actively seek out information and internal solutions to ensure reusability and adoption of common technologies

Qualifications

• 3 years of experience in the field with focus on NLP
• Previous software engineering experience is preferable
• Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data)
• Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics
• Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle
• Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes
• The ability to design solutions using common design patterns and various design tools
• Experience in experiment design and the ability to validate the credibility of information from various sources
• A solid understanding of the business value of delivered features
• Strong problem solving skills, with an emphasis on using technical facts and reasoning
• Excellent communication and collaboration skills, including active listening and the ability to build consensus
• A strong drive for continuous self development and a collaborative mindset for contributing to communities

Conditions & Benefits

• Stable salary, official employment
• Health insurance
• Hybrid work mode and flexible schedule
• Relocation package offered for candidates from other regions
• Access to professional counseling services including psychological, financial, and legal support
• Discount club membership
• Diverse internal training programs
• Partially or fully payed additional training courses
• All necessary work equipment