Dan T.
Lead Data Scientist / AI Platform Engineer
Experience
Apr 2024 - Present
1 year 9 monthsLead Data Scientist / AI Platform Engineer
Tkxel
- Led design and deployment of an internal LLM-based assistant platform serving over 1,000 daily users, improving response accuracy by 28% and reducing inference cost by 15% through optimized RAG pipeline orchestration.
- Developed company-wide AI governance framework with model observability and safety layers, ensuring compliance and reducing hallucination incidents in customer-facing models.
- Built modular RAG 2.0 pipelines using LangChain and custom orchestration to enable dynamic context retrieval across product domains.
- Partnered with data engineering teams to align feature store schemas with ML and analytics workflows, accelerating model iteration.
- Mentored junior engineers on LLMOps best practices and scalable deployment strategies across cloud and on-prem environments.
- Tech & Tools: GPT-4/5 APIs, Llama 3, LangChain, HuggingFace, Pinecone, Weaviate, Ray, KServe, MLflow, Kubeflow, Airflow, Feast, Evidently, Prometheus, AWS/GCP
Mar 2021 - Apr 2024
3 years 2 monthsSenior Machine Learning Engineer (NLP Focus)
Meta
- Led fine-tuning and deployment of transformer-based models for document intelligence, boosting text extraction accuracy by 21% and cutting inference latency by 35% through efficient model serving.
- Designed and implemented scalable ML pipelines and retraining workflows, reducing manual retraining cycles by 40% and improving model monitoring coverage organization-wide.
- Built end-to-end NLP components including tokenization, embeddings, and evaluation systems to support enterprise search and knowledge extraction.
- Pioneered early retrieval-augmented generation (RAG) prototypes for internal document Q&A solutions.
- Collaborated with platform teams to integrate ML observability and CI/CD automation within Kubernetes-based workflows.
- Conducted comparative A/B testing between transformer-based and conventional NLP models for production-grade deployment decisions.
- Acted as a mentor and reviewer for junior engineers, standardizing best practices for NLP experimentation and deployment.
- Tech & Tools: HuggingFace Transformers, BERT, RoBERTa, T5, GPT-3 API, Sentence Transformers, MLflow, DVC, Kubeflow, SageMaker, Feast, Evidently, Spark, Kafka, Delta Lake
Jun 2018 - Feb 2021
2 years 9 monthsMachine Learning Engineer
Semantic Visions
- Designed and deployed end-to-end ML microservices for recommendation and NLP features, ensuring reliable model serving and monitoring.
- Implemented A/B testing frameworks for ML system evaluation, improving iteration speed and data-driven decision making.
- Collaborated on MLOps pipeline development, including CI/CD workflows, model versioning, and automatic retraining.
- Partnered with data engineering teams to optimize ETL and feature pipelines using Spark and Airflow.
- Contributed to early adoption of MLflow and model observability dashboards, improving transparency across deployed models.
- Tech & Tools: TensorFlow 2.x, PyTorch, scikit-learn, BERT, Docker, Airflow, Kubernetes, Flask/FastAPI, MLflow, Spark, Kafka, BigQuery, Prometheus, Grafana
Nov 2016 - May 2018
1 year 7 monthsData Engineer
Featurespace
- Designed and implemented ETL-to-ELT data pipelines using Spark and Airflow, enabling near real-time analytics for product metrics.
- Migrated key data workflows from on-premise to AWS and GCP, improving reliability and reducing latency.
- Built and maintained data marts and semantic layers supporting downstream analytics and early machine learning projects.
- Introduced Kafka streaming for processing event data, increasing scalability and monitoring capabilities.
- Partnered with analysts and data scientists to create efficient feature-ready data pipelines for experimentation.
- Tech & Tools: Python 3, SQL, Airflow, Spark, Hive, Kafka, AWS (Redshift, S3), GCP (BigQuery), Docker, Bash
Oct 2015 - Nov 2016
1 year 2 monthsJunior Data Engineer (Analytics & ETL)
UiPath
- Automated legacy Excel/VBA reports using Python and SQL, significantly reducing manual reporting cycles.
- Assisted in building initial BI dashboards and ETL pipelines supporting executive analytics.
- Participated in pilot Hadoop/Hive projects to evaluate distributed data processing for large datasets.
- Tech & Tools: SQL (MySQL, Postgres), Python 2.7/3, Excel/VBA, Tableau, Power BI, Linux, Bash
Summary
Senior Machine Learning Engineer with a strong hybrid foundation in data science, MLOps, and AI platform development, bridging the gap between scalable machine learning systems and business-driven modeling strategies. Over 10 years of experience spanning data engineering, ML infrastructure, NLP, and LLM-based applications, driving measurable impact through model performance optimization, experimentation, and production reliability. Adept at leading cross-functional ML initiatives, mentoring teams, and transforming complex data pipelines into deployable, value-oriented AI solutions across cloud environments.
Languages
Vietnamese
NativeEnglish
AdvancedEducation
Sep 2017 - Aug 2019
University of York
Master of Science in Computer Science · Computer Science · York, United Kingdom
Sep 2011 - Jun 2015
Hanoi University of Science and Technology
Bachelor of Science in Computer Science · Computer Science · Hanoi, Viet Nam
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