Anmol S
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The client satisfaction rating is the weighted average of client ratings, with weights based on reviewed work hours. When no client rating exists, the approval fraction (approved vs. reviewed work hours) determines it.
If the client satisfaction rating exceeds the overall rating, it becomes the star rating. In the absence of client ratings, if the average client interview rating is higher than the overall rating, it becomes the star rating. If no data is available, the star rating defaults to the internal interview score.
Machine Learning Engineer Preferred Title
$36.25 /hr $ 80.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Average Count of Messages/Day 0.7
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 30h PST, 26h UTC
- Software Engineering Process 4.0/5
- Design Practice 3.0/5
- Design Theory 3.0/5
- Technical Breadth 4.0/5
- Logical Thinking 5.0/5
- Technical Strength 5.0/5
- System Design 3.0/5
- Productivity and Responsiveness 3.0/5
- Teamwork 4.0/5
- Agile Development Process 3.0/5
- Intellectual Merit 5.0/5
- English Communication 4.0/5
- Documentation 3.0/5
- Desktop Mac
- Phone iPhone
- Tablet iPad
- Member Since Dec 12, 2023
- Profile Last Updated Feb 06, 2024
- Last Activity June 19, 2024, 5:10 p.m. UTC
- Location United States of America
- Current Status Student
Profile Summary
With a robust background in Large Language Models (LLMs), Natural Language Processing (NLP), deep learning, and data science, I have demonstrated success in diverse domains through transformative projects. Skilled in orchestrating end-to-end machine learning initiatives and leveraging cloud platforms like AWS and GCP for scalability, my expertise lies in transforming complex data into actionable insights. Passion-driven for creating AI solutions, I aim to generate tangible, real-world impact.
Skills
Total Experience: 3 years
Python (4E, 3Y)
4 experiences, across 3 yearsTensorflow (2E, 3Y)
2 experiences, across 3 yearsAWS (2E, 2Y)
2 experiences, across 2 yearsFlask (2E, 2Y)
2 experiences, across 2 yearsGoogle Cloud Platform
Rest Api
Product Lifecycle Management (2Y)
2 years of experienceDeep learning (2Y)
2 years of experienceContinuous Delivery (2Y)
2 years of experienceAgile (2Y)
2 years of experienceLLM Large Language Models (2E)
2 experiencesVector Spaces (2E)
2 experiencesDocker (3E)
3 experiencesMongoDB
AWS S3 (2E, 2Y)
2 experiences, across 2 yearsFastAPI
Open AI
Amazon Elastic Kubernetes Service
React native
AWS Redshift
Apache Airflow
ETL Extract Transform Load
dbt
Terraform
Datalake
Apache Kafka
AWS Lambda
AWS Glue
Pyspark
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 30h PST, 26h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
16 - 23
17 - 20
17 - 20
17 - 20
17 - 20
17 - 20
15 - 23
PST
09 - 16
10 - 13
10 - 13
10 - 13
10 - 13
10 - 13
08 - 16
Vetting
- Interview Data
- Software Engineering Process
- Design Practice
- Design Theory
- Technical Breadth
- Logical Thinking
- Technical Strength
- System Design
- Productivity and Responsiveness
- Teamwork
- Agile Development Process
- Intellectual Merit
- English Communication
- Documentation
- Code Quality
- Code Readability
- Soft Skill Attributes
- Project Management Ability
Experience
Machine Learning Engineer
Passion Project
Oct 2023 - Dec 2023
University of Wisconsin-Madison Company
Technology Industry
Project: GitGpt
- Developed a scalable semantic search platform, enhancing GitHub codebase interactions using power of LLM Large Language Models and Open AI api.
- Other technologies used to make it a modular and scalable application are Docker, FastAPI, Amazon Elastic Kubernetes Service, Vector Spaces, LangChain Framework, Llama-2 (LLM), and React native .
Machine Learning Engineer
Internship
May 2023 - Sep 2023
Catalyst Management Services Company
Technology Industry
Project: Semantic search engine
- Engineered an innovative machine learning pipeline for a semantic search engine using LLM Large Language Models, enhancing data extraction and analysis using Python.
- Used Regex for precise data preprocessing and used NLP techniques with models like BERT for advanced sentiment analysis, aspect identification, statistics extraction, and summary generation.
- Developed and deployed a responsive chat system using Vector Spaces and the LangChain framework, demonstrating capabilities in AI-driven query response systems.
- Able to achieve a 15% increase in data retrieval efficiency for web-scraped climate change and healthcare articles.
- Effectively managed a Docker Flask application on AWS, integrated MongoDB with VectorDB, and implemented continuous monitoring, ensuring data integrity and the seamless operation of the data pipeline.
Student
Passion Project
Jun 2023 - Jul 2023
University of Wisconsin-Madison Company
Project: Reddit-Analytics-Integration-Platform
- Implemented an ETL Extract Transform Load pipeline using python, AWS S3, AWS Redshift, dbt, Apache Airflow, and Docker to extract insights from subreddit, resulting in 5% increase in data processing.
- Transformed raw Reddit data into actionable insights using Google Data Studio/ Tableau, leading to the identification of 15 key trends in data , and optimized project cost using Terraform.
Co-founder, CTO
Employment
Apr 2022 - Mar 2023
Epiassist Pvt. Ltd. Company
Technology Industry
Project: Deep learning based system to predict Epilepsy seizure
- Led a team in developing an anomaly detection deep learning algorithm for detecting epileptic seizures from physiological data collected via our smart band.
- Utilized Tensorflow and Python for the project and processed multivariate time-series data.
- Oversaw product lifecycle management, implemented ETL data pipeline, utilized Agile methodologies, and employed continuous delivery for product development and deployment on AWS.
Passion Project
Nov 2022 - Dec 2022
Company
Technology Industry
Project: StreamLytics: Real-Time Machine Learning Pipeline for Music Streaming Insights
- Engineered a Apache Kafka and Pyspark streaming-based data pipeline for a music streaming simulation, achieving a 20% improvement in genre class. accuracy through PCA optimization.
- Automated batch processing and data transformation with Apache Airflow, enhancing efficiency by 15% and enabling real-time analytics on Google Cloud Platform.
- Developed dynamic Google Data Studio dashboards for user behavior and song popularity insights, supporting strategic, data-driven decision-making.
- AWS services used in project: AWS S3, AWS Athena, Quicksight, AWS Glue, AWS lambda AWS datalake, Python.
Machine Learning Engineer
Contract
Jan 2021 - Dec 2021
Indian Institute of Information Technology Company
Project: Develop Machine Learning IoT framework to monitor health of dairy animal
- Created an ML-driven collar for dairy cattle health monitoring, with a focus on activity analysis and predictive modeling for reproductive health.
- Implemented an end-to-end, input-to-prediction scalable pipeline using TensorFlow, managing both data and model drift.
- Developed and deployed a machine learning model using Google Cloud Platform's Vertex AI platform to empower a real-time health analysis REST API, built with Python and Flask.
- Built a dashboard using Google Data Studio to display statistics.
Qualifications
Education
University of Wisconsin-Madison
Sep 2022 - May 2024
Master of Science (Computer Engineering)