Muhammad R.

Key Skills

Software

Don't disclose

Top Subject Matter

Generative AI/LLMs

Rag Domain Expertise

agentic workflows

Top Data Types

Text

Image

Top Task Types

Fine-tuning

Data Collection

Freelancer Overview

Lead AI/ML Engineer (Generative AI systems development with prompt/LLM evaluation and fine-tuning practices). Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Master of Science, Lahore University of Management Sciences (LUMS). AI-training focus includes data types such as Text and labeling workflows including Fine-tuning, Evaluation, and Rating.

Labeling Experience

Lead AI/ML Architect - P2H

Text

Architected and delivered enterprise-grade Generative AI solutions by translating business problems into scalable AI products. Designed systems using LLMs, Retrieval-Augmented Generation (RAG), and agentic multi-agent orchestration frameworks to meet performance and availability needs. Led governance, security, observability, and evaluation practices to support responsible deployment of production GenAI applications. • Built cloud-native AI platforms integrating foundation models with vector databases and knowledge retrieval pipelines. • Partnered with business stakeholders and engineering leadership to define AI roadmaps and prioritize high-impact automation. • Established standards for prompt engineering, model evaluation, fine-tuning, and LLM application development. • Directed MLOps and LLMOps initiatives including CI/CD, monitoring, and lifecycle management of AI systems.

2022 - Present

Lead AI/ML Engineer (Generative AI systems development with prompt/LLM evaluation and fine-tuning practices)

Don't discloseTextFine-tuning

Led end-to-end development of generative AI systems that required creating and curating prompt and response datasets for reliable LLM application behavior in production. Designed evaluation and governance frameworks to assess model outputs and iterate on dataset/label quality for better performance and responsible deployment. • Established standards for prompt engineering, model evaluation, and fine-tuning practices. • Built LLM/RAG systems that rely on labeling-like curation of knowledge and retrieval outputs. • Implemented observability and evaluation loops to improve response quality and reliability. • Mentored teams on LLM application development workflows aligned to governance and safety.

2022 - Present

Senior Machine Learning Engineer (training-data preparation and model evaluation for NLP/ML deployments)

Don't discloseText

Developed and deployed machine learning and deep learning solutions including NLP components that required preparing training data and validating model outputs through experimentation. Contributed to end-to-end ML pipelines from preprocessing and feature engineering through training and deployment, including evaluation and reliability improvements. • Built predictive models and deep learning applications using common ML frameworks and validation workflows. • Delivered NLP solutions and integrated trained ML components into backend APIs for real-world use. • Refined model performance using systematic experimentation, validation, and continuous improvement. • Mentored junior engineers and supported establishment of ML best practices and technical standards.

2019 - 2022

Software Engineer (Machine Learning) (data preparation and training workflow support)

Don't discloseTextData Collection

Supported machine learning initiatives by implementing data processing pipelines, model training workflows, and early-stage predictive models. Performed data collection, cleaning, and feature engineering to improve data quality, then participated in model evaluation and debugging to enhance reliability. • Collected, cleaned, and engineered features to improve model accuracy and data quality. • Contributed to NLP and computer vision proof-of-concept foundational models. • Helped integrate ML components into software applications with supporting backend tasks. • Participated in model evaluation and debugging for performance and reliability gains.

2016 - 2019

Education

Work History