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AI Engineer with 1+ years in computer vision, deep learning, and MLOps.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer with hands-on experience in computer vision, object detection, and deep learning. Proven ability to build end-to-end machine learning pipelines from data preprocessing to model deployment. Proficient in Python, TensorFlow, and modern ML frameworks. Seeking to leverage technical expertise and passion for innovation in a challenging role at Google.
Vivekananda Global University
Bachelor of Technology · Artificial Intelligence
August 1, 2022 – June 30, 2026
Happy Health Innovation Pvt. Ltd.
AI/ML Intern
November 1, 2024 – Present
Jaipur, Rajasthan, India
CodeSoft
AI/ML Developer
July 1, 2024 – August 31, 2024
Jaipur, Rajasthan, India
MLOps Deployment Framework
June 1, 2026 – June 30, 2026
Containerized ML models using Docker for consistent deployment across environments Built REST APIs using Flask for model serving and integration with web applications Implemented version control and CI/CD practices for reproducible ML workflows
Python Certification
GeeksforGeeks
June 1, 2026 – Present
AI Tools Workshop
Be10x
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's involvement in a coding competition and open-source contributions suggests a proactive and engaged individual. The project diversity, though limited to personal and internship projects, shows an interest in applying AI/ML to real-world problems (e.g., healthcare automation). The target role of 'AI Engineer' aligns well with the candidate's stated skills and project experience, particularly in ML pipelines and deployment. However, the overall experience level is still junior, which might impact fit for a senior-level role requiring extensive independent decision-making and leadership.
Soft Skills & Operational Fit
The candidate's resume indicates collaboration with cross-functional teams and documentation of technical processes, suggesting a foundational understanding of teamwork and operational best practices. However, without specific psychometric or English test results, a deeper assessment of soft skills and operational fit is limited.