# Aneesh Naik

> Software Engineer

Location: Boston, Massachusetts, United States
Profile: https://flows.cv/aneeshnaik

Software developer with expertise in web development, machine learning (specifically NLP), data analysis and visualization. 

Programming languages: Python, JavaScript, SQL, R. Some familiarity with HTML & CSS. 
Web frameworks: Django, Flask, FastAPI
Cloud: AWS, GCP, Heroku
DevOps: Git, Docker, Kubernetes
ML libraries: Pytorch, Scikit-learn, Spark MLlib, Huggingface Transformers, Spacy
Data viz libraries: Plotly, Altair, Matplotlib, Ggplot2, D3

## Work Experience
### Senior Software Engineer @ Teikametrics
Jan 2025 – Present

### Software Engineer II @ Teikametrics
Jan 2022 – Present

### Software Developer - Backend @ MIT Media Lab
Jan 2020 – Jan 2022 | Cambridge, Massachusetts, United States
Worked on backend systems for web-based research projects built using Django.

Defined schemas and set up PostgreSQL databases for collection of user provided speech data collected via Twilio IVR flows. Exposed collected data via RESTful APIs to power the frontends.

Developed data processing pipelines for transcription, timestamp generation and annotation of collected speech data. 

Set up machine learning infrastructure using AWS Sagemaker for training and deployment of custom NLP models for real-time inference. 

Developed a python module that generated a 24/7 live video feed which served as the main content for the projects, using FFmpeg and other image processing libraries.

### Language Modeling Intern @ Cerence Inc.
Jan 2020 – Jan 2020 | Burlington, Massachusetts, United States

### Technical Fellow @ Cortico
Jan 2019 – Jan 2019 | Cambridge MA
Completed a 6-week training in data engineering best practices at the Lab for Social Machines at MIT.
 
Deployed a containerized application to a Kubernetes cluster that collected streaming data from Wikipedia’s recent changes API, using RabbitMQ as a message broker. Data was stored as compressed parquet files on S3.

Developed a novel topic modeling algorithm based on density based clustering of document embeddings, used to automatically discover topics in hundreds of hours of transcribed speech data.

### Research Assistant @ Phonetics and Phonology Lab, UMass Amherst
Jan 2017 – Jan 2019 | Amherst, MA
Designed experimental audio stimuli for phoneme categorization using praat.

Analyzed categorical and temporal speech perception data with R using statistical methods such as hypothesis testing, regression analysis and mixed effect models.

Published an abstract for a study exploring the interaction between speaking rate and phoneme perception: https://asa.scitation.org/doi/abs/10.1121/1.5101945


## Education
### Linguistics
University of Massachusetts Amherst

### Summer School in Linguistics
University of Crete

### Summer School
Hampshire College


## Contact & Social
- LinkedIn: https://linkedin.com/in/aneesh-naik-b7b0b112a
- GitHub: http://github.com/aneesh3397

---
Source: https://flows.cv/aneeshnaik
JSON Resume: https://flows.cv/aneeshnaik/resume.json
Last updated: 2026-03-31