Vikram Kumar (mrvkparmar)

Machine Learning & Data Engineering practitioner with hands-on experience building Transformer-based NLP pipelines (RAG, LLM inference, prompt engineering) and production-grade, large-scale data infrastructure (Airflow, Spark, Kafka, distributed processing). Currently serving as Campus Ambassador for Devsinc and atomcamp, driving AI-focused community engagement alongside applied ML project work. Strong foundation in Python, applied statistics, and experimental design; passionate about training, evaluating, and deploying state-of-the-art models and eager to contribute as a Machine Learning Intern.

Machine Learning & Data Engineering Intern (Freelance) at Self-Employed (2024-03 – Present)

• Designed and improved Python-based ML data pipelines feeding model training and inference workflows, cutting manual processing overhead by 30+ hours per week and increasing pipeline throughput by 90%, reflecting practical ownership of production-grade ML infrastructure.
• Built scalable REST API integrations to ingest and normalize data from heterogeneous external services, applying structured validation and cleaning techniques that improved dataset reliability by 80%, directly improving the quality of inputs used for model training and evaluation.
• Implemented data preprocessing and feature engineering workflows using linear algebra and statistical methods (normalization, imputation, outlier detection), preparing structured datasets for supervised and unsupervised model training.
• Authored reproducible engineering documentation for research methodologies and technical workflows, ensuring experiment traceability and publication-quality handoff readiness.
• Prototyped multimodal data-handling strategies, translating ambiguous requirements into well-defined algorithmic solutions with measurable evaluation criteria, demonstrating strong problem-solving and communication skills.

Data Science Intern at DevelopersHub Corporation (2025-03 – 2025-04)

• Contributed to applied data science projects, performing data cleaning, exploratory analysis, and model development under mentorship, strengthening practical skills in the end-to-end machine learning workflow.
• Collaborated with a cross-functional team to translate business problems into structured data science tasks, applying statistical and ML techniques to deliver actionable insights.

Computer Operator at The Spirit Public School (2022-10 – 2023-08)

• Managed institutional digital records systems, ensuring data integrity, accuracy, and accessibility across administrative reporting workflows and structured information repositories.

Bachelor of Science in Data Science – National University of Computer & Emerging Sciences (FAST-NUCES) (2023)

Intermediate in Pre-Engineering – Kainaat Public College (2020 – 2022)