Rohit Raj

Data Scientist

Bengaluru, Karnataka, India2 yrs 9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

2+ years of industry experience in Data Science.
Published research in IEEE IJCNN 2023.
Expertise in deep learning and NLP applications.

Stackforce AI infers this person is a Data Scientist specializing in AI and machine learning solutions for automotive and software industries.

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Skills

Core Skills

Machine LearningDeep LearningNatural Language ProcessingComputer Vision

Other Skills

3D Object DetectionApplied Machine LearningBERT (Language Model)Bug Mitigation StrategiesCode ReviewsCode-LLM TestingData AnalyticsData Pipeline EngineeringData StructuresDecision TreesDynamic Object ClassificationExploratory Data AnalysisFastAPIGPT-4Generative AI

About

I am a Data Scientist with 2+ years of industry experience and 2 years in academia, specializing in deep learning, NLP, and computer vision. My expertise spans LLMs, AI agents, RAG, LoRA, and model optimization, with applications in autonomous systems, recommendation engines, and generative AI. Previously in Mercedes-Benz R&D, I have worked on object classification, large-scale data pipelines, model optimization (QAT, TensorRT), and LLaMA-based AI agents. I have also implemented RAG + LoRA for enhanced code completion. Previously, at IISc, my research on robust NLP models led to IEEE IJCNN 2023 and SAIL 2023 publications. I also hold a patent on sensor calibration using contrastive learning. ⚡ Key Skills: Deep Learning | LLMs | VLMs | Recommender System | AI Agents | RAG | LoRA | PyTorch | TensorFlow | ONNX | AWS | ML Deployment | Airflow | Databricks| RESTAPI | Flask | Streamlit Passionate about building scalable AI solutions and pushing the boundaries of LLMs and intelligent AI systems. Let’s connect!

Experience

2 yrs 9 mos

Total Experience

1 yr 8 mos

Average Tenure

1 yr 1 mo

Current Experience

Meesho

Data Scientist

Apr 2025 – Present · 1 yr 1 mo · Bengaluru, Karnataka, India · On-site

Mercedes-benz research and development india

2 roles

Machine Learning Engineer

Aug 2023 – Apr 2025 · 1 yr 8 mos · On-site

Dynamic Object Classification
Developed, tested, and deployed sequential model for dynamic object tracking, enhancing system accuracy by 8%.
Engineered a robust data pipeline capable of processing over 4000 hours of in-house data, significantly improving model generalization .
Handled long-tailed data distributions of data, achieving a 4% reduction in validation error.
Implemented Quantization Aware Training (QAT) to optimize the model, reducing inference time by 20%,
decreasing the model size by one-third, and generating an ONNX model to enhance real-time application
performance.
Leveraged ML workflows for efficient training and validation of deep learning models.
Conducted multiple critical code reviews, elevating overall code quality and maintaining best practices
Collaborated closely with cross-functional teams, including product owners, to translate complex business problems into actionable data science solutions
Improving Code-LLM Accuracy on Buggy Code Completion
Curated an internal dataset with 1,000+ buggy code examples to test Code-LLMs in realistic scenarios.
Identified a 50%+ drop in model pass rates in buggy contexts, revealing key robustness gaps.
Applied bug-mitigation strategies like removal-then-completion and rewriting-then-completion, improving model accuracy by 20%.

Dynamic Object ClassificationData Pipeline EngineeringQuantization Aware Training (QAT)Model OptimizationML WorkflowsCode Reviews+2

Machine Learning Intern

Apr 2023 – Jul 2023 · 3 mos · On-site

Developed and deployed a high-performance 3D object detection model optimized for on-device applications, improving detection accuracy and responsiveness.
Leveraged a diverse range of datasets for comprehensive training and validation, achieving a 6% Mean Average Precision (MAP) improvement over existing models.
Implemented model optimizations using ONNX and TensorRT, resulting in a 20% reduction in inference time, thereby enhancing real-time application performance

Indian institute of science (iisc)

Research Assistant

Dec 2022 – Mar 2023 · 3 mos · Bengaluru, Karnataka, India · On-site

Implemented SOTA models for text and vision domains, effectively handling low-data regimes and maintaining high accuracy.
Engineered a robust architecture that outperformed existing models by 9% in the text domain under low-data conditions.
Set new performance benchmarks and contributed to academic research, resulting in a publication at the IEEE International Joint Conference on Neural Networks (IJCNN) 2023.