Kshitij Saxena

AI Engineer

https://www.opentalent.in/kshitij-saxena

AI Engineer with less than a year in Generative AI & Machine Learning

Arrdas Studio

Key Strengths

Strong foundational knowledge in AI/ML, LLMs, and Generative AI, demonstrated through multiple internships and projects.
Practical experience in developing and deploying production-grade AI systems, including RAG pipelines and backend integrations.
Proficiency in a wide array of relevant technologies and tools, including TensorFlow, PyTorch, LangChain, Flask, PostgreSQL, and cloud platforms (AWS, GCP).
Experience with large-scale data engineering for LLM training and fine-tuning, including multilingual datasets.
Demonstrated ability to evaluate AI model performance using metrics like BLEU, COMET, ROUGE, and BERTScore.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

Highly motivated AI/ML Engineer Intern with 8 months of hands-on experience in developing and deploying production-grade Generative AI systems. Proven ability in integrating LLM-driven solutions, building scalable backend systems, and designing advanced RAG pipelines. Possesses strong technical skills in Python, TensorFlow, PyTorch, LangChain, and Neo4j, with a focus on delivering innovative solutions in AI, machine learning, and data engineering domains.

Top Skills

PandasPythonOpenai

Education

Guru Gobind Singh Indraprastha University, Delhi

Bachelor of Technology · Industrial Internet of Things

August 1, 2023 – June 30, 2027

Dr. Virendra Swarup Public School, Kanpur

Class 12 (ISC)

N/A – May 31, 2022

Experience

Arrdas Studio

AI/ML Intern

November 1, 2025 – January 31, 2026

New York City, New York, United States

IIT Indore

Research Intern

May 1, 2025 – July 31, 2025

India

NIT Kurukshetra

Research Intern

May 1, 2025 – June 30, 2025

India

Key Strengths

Strong foundational knowledge in AI/ML, LLMs, and Generative AI, demonstrated through multiple internships and projects.
Practical experience in developing and deploying production-grade AI systems, including RAG pipelines and backend integrations.
Proficiency in a wide array of relevant technologies and tools, including TensorFlow, PyTorch, LangChain, Flask, PostgreSQL, and cloud platforms (AWS, GCP).
Experience with large-scale data engineering for LLM training and fine-tuning, including multilingual datasets.
Demonstrated ability to evaluate AI model performance using metrics like BLEU, COMET, ROUGE, and BERTScore.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's profile shows a strong alignment with an innovative and research-driven culture, evidenced by multiple research internships and participation in a national hackathon. Their work on diverse AI applications, from electricity billing to multilingual translation and exam generation, suggests a broad interest in applying AI to various problems. The use of modern tools and frameworks (e.g., LangChain, Neo4j, Streamlit) indicates a proactive approach to adopting new technologies, which is beneficial for a dynamic AI engineering role. The candidate's academic background in Industrial Internet of Things further broadens their perspective on real-world applications of AI.

Soft Skills & Operational Fit

The candidate demonstrates strong problem-solving skills through their project work, particularly in designing and deploying complex AI systems. Their experience in automating workflows and optimizing processing times suggests an operational mindset focused on efficiency. The diversity of their internship experiences indicates adaptability and a willingness to learn new domains. While direct evidence of team collaboration is limited to project descriptions, the nature of their internship roles implies working within a structured environment.