Nlp Engineer

Hard Skills

- Natural Language Processing & Understanding

- Transformer-based Models (BERT, GPT-4, RoBERTA)

- Deep Learning Frameworks (PyTorch, TensorFlow)

- Large Language Model Fine-tuning & Prompt Engineering

- Text Preprocessing & Tokenization (spaCy, Hugging Face Tokenizers)

- Building NLP Pipelines with Apache Spark & Kafka

- Model Deployment & Monitoring (TorchServe, MLflow, Kubernetes)

- Data Annotation & Augmentation

- SQL & NoSQL Databases (PostgreSQL, MongoDB)

- Cloud Platforms (AWS SageMaker, Azure AI, GCP AI Platform)

Soft Skills

- Analytical Thinking & Problem Solving

- Cross-Functional Collaboration

- Technical Leadership & Mentoring

- Agile Development Methodologies

- Effective Communication of Complex Concepts

- Innovation & Continuous Learning

*Senior NLP Engineer | TechSolutions Inc. | New York, NY*

June 2022 – Present

- Led the development of a contextual chatbot powered by transformer models, increasing customer satisfaction scores by 20%.

- Designed and deployed an NLP pipeline for automated document classification, reducing manual processing time by 45%.

- Fine-tuned GPT-4 to enhance domain-specific customer support, implementing prompt engineering strategies that improved response accuracy.

- Collaborated with data engineers to optimize distributed training workflows on AWS, decreasing model training time by 30%.

- Mentored junior NLP engineers, fostering best practices in model development and deployment.

NLP Scientist | InnovateAI Solutions | San Francisco, CA

August 2018 – May 2022

- Developed an entity recognition system that integrated with client CRMs, increasing data extraction efficiency by 35%.

- Researched and implemented transfer learning techniques to adapt pre-trained models for legal document analysis.

- Led the creation of a multilingual sentiment analysis tool, capable of analyzing social media data across five languages.

- Co-authored two papers at top NLP conferences on zero-shot learning and model explainability.

*Machine Learning Engineer | DataMind Analytics | Boston, MA*

January 2016 – July 2018

- Engineered NLP features for predictive analytics in finance, improving churn prediction accuracy by 15%.

- Built scalable data pipelines using Spark and Kafka for real-time sentiment monitoring of market news.

- Contributed to open-source NLP project libraries, adding modules for improved tokenization and model interpretability.

**Master of Science in Computer Science**

Massachusetts Institute of Technology (MIT), Cambridge, MA

Graduated: May 2015

**Bachelor of Science in Computer Engineering**

University of California, Berkeley, CA

Graduated: May 2013

- Certified TensorFlow Developer | TensorFlow Institute | 2021

- AWS Certified Machine Learning – Specialty | Amazon Web Services | 2022

- Advanced NLP with Transformers | DeepLearning.AI | 2023

**Universal Language Understanding Platform**

Designed an extensible NLP framework integrating transformers and reinforcement learning for multilingual semantic understanding, significantly reducing language-specific model training costs.

**AI-Powered Medical Records Summarizer**

Led development of a summarization system that extracts key insights from electronic health records, achieving 92% accuracy in clinical information retention and used to aid physicians in quick diagnostics.

**Customer Feedback Analyzer**

Built a sentiment classification engine leveraging RoBERTa, deploying on AWS Lambda for real-time analysis of customer reviews across e-commerce platforms.

- Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, spaCy

- Cloud: AWS (SageMaker, Lambda, EC2), GCP AI Platform, Azure Cognitive Services

- Orchestration & Infrastructure: Docker, Kubernetes, Jenkins

- Data Processing: Apache Spark, Kafka, Airflow

- Python (Expert)

- SQL (Intermediate)

- Bash scripting (Basic)