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ML Engineer with 1+ years in Machine Learning & Cloud
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring ML Engineer with a strong foundation in Machine Learning, Data Concepts and Python Programming. Skilled in building end-to-end ML pipelines and deploying scalable models. Passionate about bridging the gap between Machine learning and production systems. Seeking a challenging ML role where I can blend technical depth with business impact to solve real-world problems.
KDK College of Engineering, Nagpur
B. Tech · Computer Science & Engineering
N/A – June 30, 2024
Randstad Digital Pvt. Ltd.
Associate Process Executive
September 1, 2025 – November 30, 2025
India
ARC Technologies
Data Science & Analytics Trainee
October 1, 2024 – June 30, 2025
Nagpur, Maharashtra, India
A.D. Infocom Systems Pvt. Ltd.
Data Science intern
July 1, 2024 – August 31, 2024
Nagpur, Maharashtra, India
AD Design & Solutions Pvt. Ltd.
Python Developer intern
December 1, 2023 – March 31, 2024
India
Acmegrade Pvt. Ltd.
Cloud Computing trainee
November 1, 2022 – December 31, 2022
India
End-to-End MLOps Pipeline for House Price Prediction
June 17, 2026 – Present
Built a complete ML pipeline from data ingestion → preprocessing → training → deployment. Co-developed ML Models & Worked on model optimization and hyperparameter tuning. Used MLflow for experiment tracking and model registry. Implemented MLOps practices like CI/CD for ML, Monitoring & Retraining.
CodeBasics PowerBI Developer Professional Certificate
Unknown
June 1, 2026 – Present
MSI® Project Management Professional Certification
MSI
June 1, 2026 – Present
Certified in Research Methodology (Elite)
NPTEL
June 1, 2026 – Present
CISCO Data Science Certification
CISCO
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including a personal MLOps pipeline project and various internships in data science, Python development, and cloud computing, indicates a proactive learning attitude and broad interest in the ML/Data Science domain. The target role of ML Engineer aligns well with the candidate's stated professional summary and project experience. The breadth of skills, from core ML to MLOps and cloud fundamentals, suggests adaptability and a willingness to engage with different aspects of the ML lifecycle.
Soft Skills & Operational Fit
The candidate lists problem-solving, communication, teamwork, and collaboration as soft skills. The project descriptions and internship roles suggest some experience in collaborative environments and understanding of business rules, which are positive indicators for operational fit. However, without direct interview data, the depth of these soft skills cannot be fully assessed.