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Vipul Khatana

@vipulkhatana

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Machine Learning Engineer specializing in Deep Learning, NLP, and time-series production systems.

Austria

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What I'm looking for

I seek roles where I can build production-ready ML systems, lead MLOps and model development, and contribute to product-driven research in collaborative, growth-oriented teams.

I am a Machine Learning Engineer with 6+ years of research and engineering experience focused on deep learning, NLP, and time series analysis. I have published research, led ML initiatives that supported a €4M seed raise, and built production MLOps pipelines including automated retraining, Kubernetes deployments, and monitoring.

My background spans applied research and product engineering—developing predictive maintenance and solar PV fault models, GenAI time-series foundations, IoT-enabled products, and full-stack ML-powered applications. I combine strong analytical and leadership skills with hands-on experience in model development, cloud deployment, and customer-driven product validation.

Experience

Work history, roles, and key accomplishments

Co-Founder

Eevi Gardens

Jul 2022 - Dec 2025 (3 years 5 months)

Built IoT-enabled indoor garden product with custom electronics and app-controlled automation, secured €200k public funding and acquired paid pilot customers after 300+ customer interviews.

IoT Embedded Systems Raspberry Pi Arduino Product Development Customer Discovery Fundraising

Software Engineer

Freelance

May 2023 - Jul 2024 (1 year 2 months)

Engineered full-stack SvelteKit CRM and LLM-based Slack HR bot reducing query time by 40%, and developed a RAG-based financial document viewer achieving 10x faster performance than baseline APIs.

SvelteKit JavaScript LLM RAG Python Full Stack Developer APIs Prompt Engineering

Machine Learning Engineer

Raicoon

Jun 2019 - Jun 2022 (3 years)

Developed six ML models for solar PV fault prediction, reducing downtime by 37% and boosting operational efficiency by 22%; deployed end-to-end MLOps pipelines with CI/CD, Kubernetes, monitoring, and automated retraining.

PyTorch MLOps Kubernetes CI CD Python AWS Monitoring PostgreSQL

Research Intern

University of Vienna

Jul 2018 - Jan 2019 (6 months)

Built an ML-based predictive maintenance POC for ÖBB that demonstrated €35M annual savings potential under supervision of Prof. Dr. Torsten Möller.

Predictive Maintenance Time Series Analysis Python Data Analysis Model Evaluation

Research Intern

IIT Delhi

Jan 2018 - Jul 2018 (6 months)

Researched NLP techniques for context-based sentiment analysis of mainstream media, resulting in a COMPASS ’18 publication and recognition for applied work.

NLP Sentiment Analysis Research Python Publications

Research Intern

University of Wisconsin–Madison

May 2017 - Jul 2017 (2 months)

Implemented an mm-wave ray tracing model to collect spatial information without cameras and developed knowledge-based neural approaches to reduce training data by 85%.

Knowledge Based Neural Networks Simulation Data Efficiency

Education

Degrees, certifications, and relevant coursework

University of Vienna

Machine Learning / Data Science

2018 - 2019

Conducted a supervised project building an ML-based predictive maintenance system for ÖBB under Prof. Dr. Torsten Möller as part of graduate study activities.