◆ Building reliable ML systems
About.
Focused on production ML workflows, MLOps reliability, and scalable AI delivery.
To leverage expertise in ML, RAG, and MLOps to build reliable AI systems that scale from research to production with measurable impact.
- ▸Focused on reliable ML systems with strong data integrity and monitoring.
- ▸Experienced with MLflow pipelines and continuous learning workflows.
- ▸Built production-ready pipelines for real-time ML services.
- ▸Comfortable across ML, backend APIs, and frontend integrations.
Languages
English
German (A2)
◆ What I am working on now
Focus Areas.
Two current tracks that blend applied research with practical delivery.
◆ Technical toolkit
Skills.
Core stack across ML, backend, frontend, and MLOps tooling.
ML / Data Science
Backend
Frontend
Tools
◆ Selected work
Projects.
A mix of production ML pipelines, RAG systems, and applied research.
◆ Industry and research
Experience.
Hands-on ML engineering, MLOps, and applied research roles.
Machine Learning Engineer (MLOps)
Solid Works
Srinagar, India
Sep 2023 - Mar 2024
- ▸Engineered preprocessing pipelines to handle missing data and confounding variables.
- ▸Built Python pipelines to clean, validate, and optimize operational datasets.
- ▸Developed MLflow-based MLOps workflows for continuous learning and adaptation.
Research Assistant
National Institute Of Technology
Srinagar, India
Mar 2023 - Jul 2023
- ▸Built a real-time autonomous navigation system using a TensorFlow CNN.
- ▸Improved reliability through drift analysis and hyperparameter tuning.
React Intern
Solid Works
Srinagar, India
Jul 2021 - Jan 2022
- ▸Built responsive React apps with React Router and Redux.
- ▸Developed Node/Express APIs with MongoDB for CRUD and auth.
◆ Academic background
Education.
Formal training in data science and computer engineering.
Philipps-Universitat Marburg
M.Sc. in Data Science
Marburg, Germany
Apr 2024 - Sep 2026
University of Jammu
B.E. in Computer Engineering
Jammu, India
Aug 2019 - Sep 2023
- ▸GPA: 2.5 (Good)
- ▸Ranked among top 10% of class
◆ Start a conversation
Contact.
Open to ML engineering, RAG pipeline, and MLOps roles.
Want to collaborate or discuss ML/MLOps work? Send a message and I will get back to you.