MACHINE LEARNING DEVELOPER

DUTY & RESPONSIBILITIES: • Study and transform data science prototypes • Design machine learning systems • Research and implement appropriate machine learning algorithms and tools • Implement APIs and ensure seamless integration with external systems. • Develop machine learning applications according to requirements • Select appropriate datasets and data representation methods • Run machine learning tests and experiments • Perform statistical analysis and fine-tuning using test results • Train and retrain systems when necessary • Extend existing machine learning libraries and frameworks • Keep updated to developments in the field QUALIFICATIONS: • Proven experience as a Machine Learning Developer or similar role • Understanding of data structures, data modeling and software architecture • Deep knowledge of math, probability, statistics and algorithms • Ability to write robust code in Python, Java and/or C++ • Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) • Excellent communication skills • Ability to work in a team • Outstanding analytical and problem-solving skills • BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus. Required Skills and Expertise: • Programming Languages: Proficiency in at least one language (e.g., Python, JavaScript, Java, C++, etc.). • Data Structures & Algorithms: Strong understanding of foundational concepts. • Version Control: Experience with Git and platforms like GitHub(preferred), GitLab, or Bitbucket. • Problem-Solving: Ability to break down problems and apply logical solutions. • Debugging Skills: Familiarity with debugging tools and techniques. • Containerization Experience: Advanced experience in deploying services using Docker containers, Kubernetes and other similar deployment techniques to servers. • AWS or GCP experience: This is necessary as the work will involve deployment to these platforms. • Object-Oriented Programming (OOP) and Unit Testing: Expert in OOP principles and unit test-driven development methodologies. • Generative AI (GenAI): Basic understanding of GenAI applications. • Client Management and Project Management: Advanced skills in managing client relationships and overseeing technichal aspects of projects.