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Machine Learning Engineer with 1+ years in Generative AI & ML Systems
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer with hands-on experience in Generative AI, AI agent development, and scalable ML systems. Skilled in building LLM-based pipelines, RAG applications, and deploying production-ready solutions using modern AI frameworks. Proven ability to design intelligent systems for enterprise workflows and real-world problem solving. Strong foundation in machine learning, computer vision, and software engineering principles.
Pimpri Chinchwad College of Engineering, Pune
B.Tech · Computer Science (AI & ML)
August 1, 2022 – June 30, 2026
Dr. Chandrabhanu Sonvane Jr. College, Solapur
Class XII
June 1, 2022 – May 31, 2022
Quantiphi
Machine Learning Engineer
January 1, 2026 – Present
India
Muks Robotics AI Pvt. Ltd.
Computer Vision Intern
March 1, 2025 – September 1, 2025
India
IOH Sahabat AI (Agent-Based System)
June 24, 2026 – Present
Designed and developed an AI agent-based system using MCP for seamless multi-agent orchestration. Built and integrated MCP servers for dynamic tool calling and real-time workflow execution. Enabled scalable automation by coordinating multiple intelligent agents across enterprise use cases.
Industrial Human Safety Monitoring System
June 24, 2026 – Present
Developed a real-time human safety monitoring system for industrial environments at Tata Motors. Implemented object detection and tracking to identify unsafe conditions and personnel risks. Optimized computer vision pipelines for high accuracy and performance in live industrial settings.
Cultural Fit Analysis
The candidate's project diversity, ranging from industrial safety monitoring to agent-based systems for enterprise automation, indicates adaptability and a broad interest in applying ML solutions. The experience with modern AI frameworks (LangChain, HuggingFace, Google ADK) and protocols (MCP) shows a commitment to staying current with industry trends. The target role of Machine Learning Engineer aligns well with the candidate's stated skills and professional experience, suggesting a good cultural fit for an innovation-driven environment.
Soft Skills & Operational Fit
The candidate's resume indicates a focus on problem-solving and building impactful AI systems, suggesting a proactive and results-oriented work attitude. The project descriptions highlight collaboration (e.g., 'seamless multi-agent orchestration'), which implies good team collaboration potential. However, without specific psychometric or behavioral test results, a detailed assessment of stress handling or other soft skills is not possible.