AI Engineer with 2+ years in Conversational AI & Data Science
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Assessing your cultural and operational fit
AI/ML Engineer with 2.9 years of progressive experience in developing and deploying enterprise-grade Conversational AI chatbots, machine learning models, and data science solutions. Proficient in Python, Machine Learning, Deep Learning, and Generative AI frameworks, with a proven track record of transitioning legacy workflows into AI-powered systems, optimizing decision-making, and enhancing user engagement.
CRANES VARSITY, a Training Division of Cranes Software International Ltd
Post Graduate Diploma · Data Science and Machine Learning
August 1, 2023 – June 30, 2024
Sahrdaya College of Engineering and Technology
BTech · Computer Science and Engineering
August 1, 2019 – June 30, 2019
Synosys Technologies LLC
AI/ML ENGINEER
June 1, 2025 – Present
Kozhikode, Kerala, India
Doctosmart Enterprises Pvt Ltd
DATA SCIENCE
July 1, 2024 – April 1, 2025
Kozhikode, Kerala, India
Cranes Varsity
DATA SCIENCE INTERN
July 1, 2023 – July 1, 2024
Bengaluru, Karnataka, India
CIRCUIT BUILD AR (AUGMENTED REALITY CIRCUIT SIMULATOR)
June 24, 2026 – Present
Pioneered a virtual laboratory leveraging augmented reality to simulate and analyze electrical circuits. Monitored circuit behavior, providing valuable insights for students to understand and perform electrical interactions.
Career Essentials in Data Analysis
Microsoft and LinkedIn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience spans academic projects, an internship, and full-time roles in data science and AI/ML, indicating a diverse background and willingness to engage in various aspects of the field. The focus on practical application (chatbots, predictive models, AR simulator) aligns with a results-oriented culture. The stated soft skills also suggest a collaborative and communicative team member.
Soft Skills & Operational Fit
The candidate's resume highlights strong communication and critical thinking skills, along with the ability to present technical concepts to non-technical stakeholders. These are crucial for an AI Engineer role, especially when driving AI adoption and explaining complex solutions. The project diversity and experience in both data science and AI/ML roles suggest adaptability and a proactive approach to learning and implementation.