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Mahammad Hajiyev

Senior Software Engineer (LLM Workflow/Data Labeling)

USA flagSan Jose, Usa
Expert

Key Skills

Software

No software listed

Top Subject Matter

Operational workflow automation and internal documentation
Product data workflows and content matching
Search relevance and prioritization analytics

Top Data Types

TextText
DocumentDocument

Top Task Types

Text SummarizationText Summarization
ClassificationClassification

Freelancer Overview

Senior Software Engineer (LLM Workflow/Data Labeling). Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, Azerbaijan State Oil and Industry University (ASOIU) (2018). AI-training focus includes data types such as Text and Document and labeling workflows including Text Summarization and Classification.

Expert

Labeling Experience

Senior Software Engineer (LLM Workflow/Data Labeling)

TextText Summarization
As Senior Software Engineer, I designed and deployed LLM-powered workflows for summarization and classification, leveraging prompt templates and RAG pipelines. These workflows involved the creation, curation, and evaluation of labeled datasets for high-precision answers over internal knowledge bases. Evaluation harnesses with golden sets, offline benchmarks, and structured scoring were implemented to ensure answer quality and reduce hallucinations. • Designed, deployed, and iteratively improved LLM-based summarization/classification pipelines. • Generated, enriched, and reviewed gold-standard labeled datasets for continuous AI evaluation. • Created evaluation scripts and scorecards to benchmark and monitor ML output quality. • Collaborated with product and engineering to translate use cases into labeling/evaluation tasks.

As Senior Software Engineer, I designed and deployed LLM-powered workflows for summarization and classification, leveraging prompt templates and RAG pipelines. These workflows involved the creation, curation, and evaluation of labeled datasets for high-precision answers over internal knowledge bases. Evaluation harnesses with golden sets, offline benchmarks, and structured scoring were implemented to ensure answer quality and reduce hallucinations. • Designed, deployed, and iteratively improved LLM-based summarization/classification pipelines. • Generated, enriched, and reviewed gold-standard labeled datasets for continuous AI evaluation. • Created evaluation scripts and scorecards to benchmark and monitor ML output quality. • Collaborated with product and engineering to translate use cases into labeling/evaluation tasks.

2024 - Present

Software Engineer (ML Data Labeling & Evaluation)

TextClassification
In this role, I delivered ML-assisted product features that required generating, validating, and utilizing labeled text datasets for classification, tagging, and summarization tasks. I performed hands-on ETL validation and schema checks to enhance data quality. Evaluation practices were established for monitoring output accuracy and consistency over time. • Developed and maintained labeled datasets for ML model training and evaluation. • Applied thorough validation, deduplication, and schema enforcement to training data. • Ran and documented accuracy checks and threshold tuning on ML outputs. • Integrated ML outputs and labels into user-facing workflows and tooling.

In this role, I delivered ML-assisted product features that required generating, validating, and utilizing labeled text datasets for classification, tagging, and summarization tasks. I performed hands-on ETL validation and schema checks to enhance data quality. Evaluation practices were established for monitoring output accuracy and consistency over time. • Developed and maintained labeled datasets for ML model training and evaluation. • Applied thorough validation, deduplication, and schema enforcement to training data. • Ran and documented accuracy checks and threshold tuning on ML outputs. • Integrated ML outputs and labels into user-facing workflows and tooling.

2022 - 2024

Software Engineer (Data Enrichment & Labeling)

TextClassification
My responsibilities included data enrichment, normalization, and rule/model-based labeling of incoming structured and unstructured data for prioritization and analytics systems. I developed batch workflows for feature extraction and labeling, with processes for retries and robust pipeline quality. Evaluation scripts were built to compare and validate labeling/scoring changes before production deployments. • Labeled and enriched incoming datasets to enable downstream ML scoring. • Built feature extraction and labeling workflows for scalability and repeatability. • Created and ran batch evaluation/validation scripts for labeled data. • Defined quality thresholds and acceptance criteria for labeled ML datasets.

My responsibilities included data enrichment, normalization, and rule/model-based labeling of incoming structured and unstructured data for prioritization and analytics systems. I developed batch workflows for feature extraction and labeling, with processes for retries and robust pipeline quality. Evaluation scripts were built to compare and validate labeling/scoring changes before production deployments. • Labeled and enriched incoming datasets to enable downstream ML scoring. • Built feature extraction and labeling workflows for scalability and repeatability. • Created and ran batch evaluation/validation scripts for labeled data. • Defined quality thresholds and acceptance criteria for labeled ML datasets.

2020 - 2022

Software Developer (Data Preparation & Labeling)

DocumentClassification
I built and automated data pipelines and scripts to prepare, clean, and label both structured and unstructured records for reporting and ML analysis. Heuristic classification and clustering were used for grouping and triage, with dashboards for quality control. Dashboards and exports were created to inspect and monitor label distributions for workflow improvement. • Prepared and labeled operational datasets for reporting and ML feature engineering. • Implemented rule-based and heuristic labeling/grouping for triage workflows. • Developed quality inspection dashboards for labeled data monitoring. • Improved data consistency through validation, deduplication, and schema enforcement.

I built and automated data pipelines and scripts to prepare, clean, and label both structured and unstructured records for reporting and ML analysis. Heuristic classification and clustering were used for grouping and triage, with dashboards for quality control. Dashboards and exports were created to inspect and monitor label distributions for workflow improvement. • Prepared and labeled operational datasets for reporting and ML feature engineering. • Implemented rule-based and heuristic labeling/grouping for triage workflows. • Developed quality inspection dashboards for labeled data monitoring. • Improved data consistency through validation, deduplication, and schema enforcement.

2019 - 2020

Education

A

Azerbaijan State Oil and Industry University (ASOIU)

Bachelor of Science, Computer Science

Bachelor of Science
2013 - 2018

Work History

S

Senpex

Senior Software Engineer

San Jose
2024 - Present
B

Business Warrior

Software Engineer

Phoenix
2022 - 2024