Senior Machine Learning Engineer

Summary

Join Byborg's Machine Learning R&D team, a leader in IT and streaming solutions, and contribute to the design, development, and deployment of advanced machine learning models. Collaborate with a diverse team to solve complex business problems and build an independent ML system. Develop and maintain production-level code, transforming machine learning models and PoCs into reliable, scalable pipelines. Optimize solution performance and code efficiency, participate in code reviews, mentor junior engineers, and contribute to overall code quality. This role requires a strong background in machine learning, proficiency in Python and relevant libraries, and excellent communication and collaboration skills.

Requirements

• B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related technical field
• 6+ years of industry experience in developing and deploying ML solutions
• Proficiency in Python and experience with popular data science libraries
• Expertise in ML frameworks (both deep and classical/shallow learning) like TensorFlow, PyTorch, and Scikit-Learn
• Strong understanding of classical/shallow and deep learning algorithms, and practical experience in applying them
• Proficient in statistics methodologies and comfortable with techniques such as clustering, forecasting, regression, and classification
• Excellent problem-solving skills and a strong engineering mindset, with the ability to write high-quality, maintainable code
• Exceptional communication and collaboration skills, with a proven track record of working effectively in a team

Responsibilities

• Lead the design, development, and deployment of advanced machine learning models to solve complex business problems
• Collaborate with a diverse team of engineers, and stakeholders to brainstorm and implement innovative solutions
• Develop and maintain production-level code, transforming machine learning models, PoCs into reliable, scalable pipelines
• Partner with other Machine Learning Engineers to create, evaluate, and iterate on models
• Optimize solution performance and code efficiency to handle large-scale data and applications
• Participate in code reviews, mentor junior engineers, and contribute to the overall code quality and knowledge sharing within the team