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Senior
Armenia
Andranik brings over 7 years of experience in AI, Machine Learning, and Data Science, with strong expertise in Python across all roles. He currently leads and manages a team of 20–30 software engineers, overseeing technical direction, code quality, and cross-functional operations while working closely with clients to translate business needs into scalable technical solutions. His experience includes building and deploying AI products end-to-end, with hands-on work in PyTorch and TensorFlow, as well as practical applications in LLMs, NLP, Computer Vision, and Generative AI. He has a solid background in developing and managing ML pipelines and MLOps processes, including CI/CD, Docker, and cloud environments such as GCP and Azure. Additionally, he brings strong experience in handling complex systems, including cloud cost optimization and infrastructure decisions, alongside a unique perspective as a digital forensic expert working on code-related investigations.
Yerevan State University
Yerevan State University
• Perform digital evidence analysis and support investigative teams in complex forensic cases.
• Prepare expert conclusions and collaborate with legal professionals in both public and private sector matters.
• Lead a team of 15-20 machine learning engineers, data scientists, and analysts.
• Developed and executed MԼ strategies to enhance clinical research productivity.
• Led collaboration with diverse teams to integrate ML solutions into clinical workflows.
• Built and managed automated ML pipelines, ensuring scalable and efficient model deployment and monitoring.
• Led the development of scalable AI and ML services, consulting across different domains.
• Provided strategic advice on AI solutions, ensuring alignment with business objectives.
• Translated business requirements into effective data-driven solutions, focusing on a holistic approach to service development.
• Researched and implemented appropriate ML algorithms and tools.
• D, esigned, built, and productionized ML models to solve business challenges using Google Cloud technologies and knowledge of proven ML models and techniques.
• Automated the development and test processes through CI/CD pipeline (Gitlab, Docker containers).
• Deployed, monitored, and tested ML models, developed API for Ml models.
• Collaborated with cross-functional teams to integrate machine learning solutions seamlessly into existing systems and workflows.
• Created internal management tools API with Python.
• Manipulated Excel/CSV, PDF, JSON files with Python.
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