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AI Engineer with 1+ years in LLM Deployment & Data Structures
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Junior AI Engineer with a strong foundation in C++, Java, Python, and JavaScript, coupled with expertise in AI/ML frameworks like PyTorch and TensorFlow. Proven ability to design optimized data-processing pipelines, integrate LLM architectures, and solve complex algorithmic challenges. Eager to contribute to innovative deep learning and real-time data solutions.
Keshav Memorial Institute of Technology (KMIT)
Bachelor of Technology · Computer Science and Engineering
N/A – June 30, 2028
CrossPPI Real-Time Framework
Lead Developer & Researcher
January 1, 2025 – Present
India
Local LLM Architecture & ComfyUI Integration
AI Systems Engineer
January 1, 2025 – Present
India
Algorithmic Engineering Engine
Advanced Problem Solver
January 1, 2024 – Present
India
Cultural Fit Analysis
The candidate's project diversity, including real-time frameworks, local LLM optimization, and extensive DSA practice, indicates a strong drive for technical challenges and continuous learning. The roles align well with an AI Engineer position, demonstrating a focus on performance, optimization, and cutting-edge AI technologies. The self-deployed portfolio also shows initiative and a practical application of skills. The breadth of skills and interests suggests a candidate who is adaptable and eager to explore different technical domains.
Soft Skills & Operational Fit
The candidate's resume highlights problem-solving abilities and a proactive approach to learning and optimization. The 'Lead Developer & Researcher' and 'AI Systems Engineer' roles suggest an ability to take initiative and manage complex technical tasks. The competitive chess background indicates strategic thinking and analytical foresight. However, without direct assessment data, specific soft skills like teamwork, communication, and stress handling cannot be definitively evaluated.