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I am a Senior Software Engineer and Machine Learning Engineer specializing in ML/AI, data engineering, NLP, and large language models with over 7 years of experience. I have a solid foundation in software engineering, designing scalable ML pipelines, building and fine-tuning large language models, and delivering production-ready AI solutions. Proficient in deep learning, semantic modeling, embeddings, and information extraction, I excel with hands-on expertise in PyTorch, TensorFlow, Hugging Face, spaCy, and Snowflake. I have a proven record deploying reproducible and efficient data workflows, collaborating with cross-functional teams, and translating NLP research into impactful real-world applications across healthcare, fintech, and enterprise domains. I am passionate about creating robust AI systems that improve operational efficiencies and user experiences through innovative AI technologies.…I am a Senior Software Engineer and Machine Learning Engineer specializing in ML/AI, data engineering, NLP, and large language models with over 7 years of experience. I have a solid foundation in software engineering, designing scalable ML pipelines, building and fine-tuning large language models, and delivering production-ready AI solutions. Proficient in deep learning, semantic modeling, embeddings, and information extraction, I excel with hands-on expertise in PyTorch, TensorFlow, Hugging Face, spaCy, and Snowflake. I have a proven record deploying reproducible and efficient data workflows, collaborating with cross-functional teams, and translating NLP research into impactful real-world applications across healthcare, fintech, and enterprise domains. I am passionate about creating robust AI systems that improve operational efficiencies and user experiences through innovative AI technologies.

Razaq Jinad

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I am a Senior Software Engineer and Machine Learning Engineer specializing in ML/AI, data engineering, NLP, and large language models with over 7 years of experience. I have a solid foundation in software engineering, designing scalable ML pipelines, building and fine-tuning large language models, and delivering production-ready AI solutions. Proficient in deep learning, semantic modeling, embeddings, and information extraction, I excel with hands-on expertise in PyTorch, TensorFlow, Hugging Face, spaCy, and Snowflake. I have a proven record deploying reproducible and efficient data workflows, collaborating with cross-functional teams, and translating NLP research into impactful real-world applications across healthcare, fintech, and enterprise domains. I am passionate about creating robust AI systems that improve operational efficiencies and user experiences through innovative AI technologies.…I am a Senior Software Engineer and Machine Learning Engineer specializing in ML/AI, data engineering, NLP, and large language models with over 7 years of experience. I have a solid foundation in software engineering, designing scalable ML pipelines, building and fine-tuning large language models, and delivering production-ready AI solutions. Proficient in deep learning, semantic modeling, embeddings, and information extraction, I excel with hands-on expertise in PyTorch, TensorFlow, Hugging Face, spaCy, and Snowflake. I have a proven record deploying reproducible and efficient data workflows, collaborating with cross-functional teams, and translating NLP research into impactful real-world applications across healthcare, fintech, and enterprise domains. I am passionate about creating robust AI systems that improve operational efficiencies and user experiences through innovative AI technologies.

Available to hire

I am a Senior Software Engineer and Machine Learning Engineer specializing in ML/AI, data engineering, NLP, and large language models with over 7 years of experience. I have a solid foundation in software engineering, designing scalable ML pipelines, building and fine-tuning large language models, and delivering production-ready AI solutions. Proficient in deep learning, semantic modeling, embeddings, and information extraction, I excel with hands-on expertise in PyTorch, TensorFlow, Hugging Face, spaCy, and Snowflake.

I have a proven record deploying reproducible and efficient data workflows, collaborating with cross-functional teams, and translating NLP research into impactful real-world applications across healthcare, fintech, and enterprise domains. I am passionate about creating robust AI systems that improve operational efficiencies and user experiences through innovative AI technologies.

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Work Experience

AI Software Engineer Intern at Nextech

June 1, 2025 - Present

Designed and optimized LLM-based semantic retrieval pipelines using embeddings such as PubMed BERT, Sap BERT, and GPT combined with FAISS and HNSW, reducing query latency by 30%. Fine-tuned transformer models (LLaMA, Mistral, GPT-4, Claude) for domain-specific tasks, boosting response relevance by 22%. Built reproducible ML pipelines with Langfuse v3, MLflow, and GitHub Actions to enable versioned experiments and automated retraining. Deployed containerized inference services with FastAPI and Docker, achieving 99.9% uptime in production. Enhanced monitoring frameworks to reduce false outputs by 18% by detecting hallucinations and drift. Developed modular benchmarking pipelines tailored for clinical and biomedical applications, integrated a comprehensive LLM evaluation framework ensuring traceability and model accountability. Integrated observability using Langfuse Observations enabling detailed root cause analysis, automated experimental evaluation tools for prompt testing, and archite

AI Software Engineer Intern at Nextech, Florida, USA

June 1, 2025 - Present

Designed and optimized LLM-based semantic retrieval pipelines using embeddings from PubMed BERT, SapBERT, and GPT with FAISS and HNSW, reducing query latency by 30%. Fine-tuned transformer models like LLaMA, Mistral, GPT-4, and Claude for domain-specific tasks, improving response relevance by 22%. Built reproducible ML pipelines with Langfuse V3, MLflow, and Github Actions, enabling versioned experiments and automated retraining. Deployed containerized inference services with FastAPI and Docker, achieving 99.9% uptime in production. Developed modular benchmarking pipelines for scalable, high-performance vector search tailored for clinical and biomedical applications. Led comprehensive LLM evaluation framework design to ensure traceability and model accountability in medical scribing workflows. Integrated observability in AI pipelines for granular performance tracking and root cause analysis. Architected a hybrid LLM system integrating open-source models with commercial APIs for 99.9% u

Graduate Assistant at Sam Houston State University

August 1, 2021 - Present

Conducted NLP research using transformers and embeddings for radicalization detection, achieving 12% higher F1 scores than baseline models. Built graph neural networks (GCN, GAT) for semantic relationship modeling applied in text classification tasks. Applied deep learning techniques (CNNs, ResNet, LSTMs, U-Net) to healthcare data such as MRI tumor detection and time-series activity recognition achieving over 95% accuracy. Engineered big data workflows with PySpark and Databricks for cybersecurity and health applications. Maintained model reproducibility via MLflow tracking, containerization, and CI/CD pipelines. Developed large language models like XLNet, BERT, and GPT for actionable insights from web data, improving cybersecurity detection accuracy to 99%. Utilized graph neural network architectures to classify radical ideologies with 82% accuracy, and automated classification and segmentation methodologies for MRI scan precision and consistency. Developed mobile applications integra

Graduate Assistant at Sam Houston State University, Texas, USA

August 1, 2021 - Present

Conducted NLP research using transformers and embeddings for radicalization detection with a 12% higher F1 score than baseline models. Built graph neural networks (GCN, GAT) for semantic relationship modeling applied in text classification tasks. Applied deep learning models (CNNs, ResNet, LSTMs, U-Net) to healthcare data achieving 95%+ accuracy including MRI tumor detection and time-series activity recognition. Engineered big data workflows using PySpark and Databricks for cybersecurity and health applications. Maintained model reproducibility with MLflow tracking, containerization, and CI/CD pipelines. Leveraged machine learning to preprocess and analyze sparse, high-dimensional data for malware web traffic pattern recognition. Implemented large language models (XLNet, BERT, GPT) and NLP techniques for actionable insights from web data achieving 99% detection accuracy. Used graph neural networks to classify radical ideologies with 82% accuracy employing architectures like GCN, GAT, G

Senior Software Engineer at E-Settlement, Nigeria

June 1, 2021 - August 26, 2025

Connected and integrated Nigeria’s first MPOS (Paypad) with the central switch enabling seamless real-time financial transaction processing. Developed data-driven fraud detection systems by integrating anomaly detection algorithms into financial APIs reducing fraud losses by 25%. Built scalable Spring Boot APIs and optimized transaction pipelines increasing throughput by 20%. Implemented containerized microservices with Docker and CI/CD pipelines reducing deployment cycles by 35%. Integrated financial platforms with Mastercard MIGS and Finacle APIs strengthening payment reliability and compliance. Developed in-branch banking solutions for debit card users streamlining branch-level financial operations. Utilized JPOS for handling ISO 8583 messaging, increasing transaction volume by 60% while maintaining high security and system integrity. Designed user-friendly desktop interfaces using C# contributing to a 40% reduction in transaction processing time and enhancing customer satisfactio

Senior Software Engineer at E-Settlement, Nigeria

June 1, 2021 - August 26, 2025

Connected and integrated Nigeria’s first MPOS (Paypad) with the central switch enabling seamless real-time financial transaction processing. Developed data-driven fraud detection systems integrating anomaly detection algorithms into financial APIs, reducing fraud losses by 25%. Built scalable Spring Boot APIs and optimized transaction processing pipelines increasing throughput by 20%. Implemented containerized microservices with Docker and CI/CD pipelines cutting deployment cycles by 35%. Integrated financial platforms with Mastercard MIGS and Finacle APIs strengthening payment reliability and compliance. Developed in-branch banking solutions for debit card users, streamlining branch-level financial operations. Leveraged Spring Boot and REST APIs for seamless connection with the bank’s Finacle core banking system. Utilized JPOS for handling ISO 8583 messaging, increasing transaction volume by 60% while maintaining high security and system integrity. Designed user-friendly desktop i