Nlp Engineer in Cloud

Hard Skills

- Cloud Platforms: AWS (SageMaker, Lambda, EC2), Google Cloud (Vertex AI, Cloud Functions), Azure (AI Services, Functions)

- NLP Frameworks & Libraries: Hugging Face Transformers, SpaCy, Gensim, NLTK

- Machine Learning & Deep Learning: TensorFlow, PyTorch, scikit-learn

- Data Processing: Apache Beam, Spark NLP, Pandas, Dask

- API Development & Deployment: RESTful APIs, Docker, Kubernetes

- Version Control & CI/CD: Git, Jenkins, GitHub Actions

- Data Storage & Databases: S3, BigQuery, Cosmos DB

Soft Skills

- Complex Problem Solving & Critical Thinking

- Technical Communication & Documentation

- Agile & DevOps Methodologies

- Cross-team Collaboration

- Innovation & Continuous Learning

*Senior NLP Engineer — Cloud Tech Solutions*

San Francisco, CA* | *June 2022 – Present

- Led the development of an enterprise-grade NLP platform hosted on AWS, integrating SageMaker for model training, Lambda for serverless inference, and API Gateway for secure endpoints.

- Architected scalable text classification and entity recognition models that improved data processing throughput by 30%.

- Developed automated pipelines for model retraining and A/B testing using AWS CodePipeline, reducing deployment cycle times from weeks to days.

- Collaborated with data engineering teams to implement data anonymization and privacy controls aligned with GDPR and CCPA standards.

- Trained cross-functional teams on best practices for NLP model deployment and cloud security.

*NLP Cloud Engineer — InnovAI Cloud Services*

Remote/NYC* | *August 2018 – May 2022

- Designed and deployed cloud-based NLP pipelines for multilingual sentiment analysis, achieving 95% accuracy across 10+ languages.

- Integrated cloud-native NLP solutions with customer analytics dashboards, enhancing real-time insights for marketing teams.

- Optimized transformer-based models for latency reductions of up to 40%, enabling real-time chatbot responses.

- Managed cloud resources efficiently, reducing costs by 25% through resource auto-scaling, spot instances, and storage optimization.

- Contributed to open-source NLP projects and authored technical documentation for enterprise adoption.

*AI Developer — TechStart Inc.*

Boston, MA* | *June 2016 – July 2018

- Developed chatbot frameworks utilizing Rasa and Dialogflow, integrated with backend cloud services.

- Built and tested custom topic modeling algorithms for document clustering and summarization.

- Worked with data scientists to deploy NLP models on Azure Functions and monitor performance.

**Master of Science in Computer Science**

Massachusetts Institute of Technology (MIT) — Cambridge, MA

*2014 – 2016*

**Bachelor of Science in Computer Engineering**

University of California, Berkeley — Berkeley, CA

*2010 – 2014*

- AWS Certified Machine Learning – Specialty (2023)

- Google Professional Data Engineer (2022)

- Microsoft Certified: Azure AI Fundamentals (2021)

- **Multilingual Chatbot Deployment**: Led a team to deploy a chatbot capable of understanding and responding in 15+ languages using fine-tuned BERT models on Google Cloud. Integrated multilingual models with Dialogflow CX, serving 1 million+ users.

- **Document Automation System**: Created a scalable document processing pipeline using AWS Textract, custom NLP models for classification and extraction, reducing processing time by 50% for legal document workflows.

- **Sentiment Analysis API**: Developed an API endpoint hosted on Azure Functions, providing real-time sentiment analysis for social media feeds, supporting over 200 million requests/month.

- English (Native)

- Spanish (Fluent)

- Mandarin (Intermediate)