Sugam K
The star rating is a representation of the overall rating, calculated as the mean of the client satisfaction rating, the average client interview rating, and internal interview scores.
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.
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
$31.25 /hr $ 15.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Worksession Approval 100.0%
- Average Response Time 9.2 hours
- Average Count of Messages/Day 3.0
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 10h PST, 38h UTC
- Earned Hours 44.00
- No. of Onboarding MCQs Completed 81
- Code Quality 1 attributes More details
- Software Engineering Process 4.0/5
- Design Practice 3.0/5
- Design Theory 3.0/5
- Technical Breadth 4.0/5
- Logical Thinking 4.0/5
- Technical Strength 4.0/5
- System Design 3.0/5
- Productivity and Responsiveness 3.0/5
- Teamwork 4.0/5
- Agile Development Process 3.0/5
- Intellectual Merit 4.0/5
- English Communication 4.0/5
- Documentation 3.0/5
- Desktop Linux
- Phone Android
- Member Since Dec 07, 2023
- Profile Last Updated Apr 24, 2024
- Last Activity March 18, 2025, 4:40 p.m. UTC
- Location Nepal
Profile Summary
I'm a highly motivated machine learning engineer dedicated to staying on the cutting edge of the field. I actively explore new concepts through research and practical projects, ensuring that I understand and apply them effectively. With a strong work ethic and a results-driven approach, I excel in translating theoretical knowledge into practical solutions. I'm eager to contribute my skills, knowledge, and passion to drive innovation in the dynamic landscape of AI and data science.
Skills
Total Experience: 3 years
PyTorch (2E, 3Y, 1C)
2 experiences, across 3 years, with 1 coursePython (2E, 3Y)
2 experiences, across 3 yearsAWS EC2 (2Y)
2 years of experienceSQL (2Y)
2 years of experiencescikit-learn (2E, 2Y)
2 experiences, across 2 yearsMachine learning (2E, 2Y, 1C)
2 experiences, across 2 years, with 1 courseOpenCV
LLM Large Language Models
Numpy
React (2Y)
2 years of experienceDjango (2Y)
2 years of experienceTensorflow (1C)
1 courseFastAPI
Deep learning (2C)
2 coursesData Analytics (1C)
1 courseRandom Forest (1C)
1 courseClassification
Linear Regression (1C)
1 coursePca (1C)
1 courseXgboost (1C)
1 courseOverfitting (1C)
1 courseMachine Learning (Theory) (1C)
1 courseData Wrangling (1C)
1 courseClustering (1C)
1 courseLogistic Regression (1C)
1 courseDeep Neural Networks (1C)
1 courseComputer Vision (Theory) (2C)
2 coursesDeep Learning (Theory) (1C)
1 courseReinforcement learning (1C)
1 courseNatural Language Processing (Theory) (1C)
1 courseNatural language processing (1C)
1 courseComputer vision (2C)
2 coursesImage Processing (1C)
1 courseImage Classification (1C)
1 courseImage Recognition (1C)
1 course
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 10h PST, 38h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Saturday
UTC
03 - 15
03 - 11
03 - 11
03 - 11
03 - 11
03 - 15
PST
20 - 08
20 - 04
20 - 04
20 - 04
20 - 04
20 - 08
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
Experience
Machine Learning Engineer
Employment
Aug 2023 - Present
Fusemachines Company
Technology Industry
Project: Product Representation
- I create a pipeline to fetch data from SQL database, run data engineering and store them in a warehouse using AWS EC2.
- I created a custom evaluation metric using cosine similarity as its base to evaluate embeddings using Python.
- I created a model capable of generating embeddings of products from customer behavior with Machine Learning Techniques using scikit-learn and PyTorch.
- I created a computer-vision-based model capable of generating the embedding of a product from one image or multiple images using PyTorch.
- I implemented multiple variation of contrastive learning algorithms using PyTorch, yielding highly representative embeddings (20% better than all other algorithms on custom metric)
Machine Learning Engineer
Employment
Jan 2023 - Jul 2023
Fusemachines Company
Technology Industry
Project: Food Recommendation System
- I compiled a report to the client on what factors might affect the recommendation using Data Analytics.
- I developed a session-based recommendation system using SOTA Deep Learning techniques in TensorFlow.
- I developed a context-aware recommendation system with a mix of Data Mining and Machine Learning techniques and Deep Learning techniques using TensorFlow.
- I developed a REST API capable of consuming recommendations using FastAPI.
Machine Learning Engineer
Course Project
Aug 2022 - Jun 2023
University of Wolverhampton Company
Healthcare Industry
Project: EncoCheck: Anomaly Detection in Digestive Endoscopy
- I created a model capable of classifying diseases in an endoscopic image and video using CNN and localizing it within the image or video using Grad-CAM with PyTorch.
- I created a full-scale web application in React which was used to provide endoscopic images and videos the the backend.
- I created a REST API using Django which served as a connection between the front-end and the machine learning model.
Machine Learning Engineer
Passion Project
Aug 2022 - Oct 2022
Self Company
Media and Communication Industry
Project: Music Genre Classification
- I created a data pipeline when given a number and genres, and generated high-quality audio features for the requested amount of songs of that genre using Python.
- I created a feature extraction system that extracts both time-domain features and frequency-domain features using Librosa.
- I created a classification model using Random Forest which classifies any short sample of an audio into a genre using scikit-learn.
LD Experience
Client Projects
Developer
Contract
Feb 2024 - Dec 2024
LD Talent Client's Company/Project
- I leveraged LLM Large Language Models and image generation models to generate high quality images from blog texts and posts using advanced prompting techniques.
- I implemented a recolor algorithm to change images to brand color using Numpy and scikit-learn
- I implemented text removal algorithm from OpenCV to remove unwanted text
Created some very nice images through AI.
Video Projects
How to implement django-tenant-schemas with a fixed URL
Sep 2020 - Jan 2022
Frontend Developer
Technology
- PyTorch
- Python
- AWS EC2
- SQL
- scikit-learn
- Machine learning
- OpenCV
- Led user research for a new construction site documentation tool.
- Hosted workshops to synthesize user insights into design requirements.
- Designed 3D concepts and built prototypes to investigate new tool form factors.
- Researched existing digital solutions and prioritized key features for app release.
LD Ventures
Thea
Sep 2020 - Jan 2022
Frontend Developer
Technology
- PyTorch
- Python
- AWS EC2
- SQL
- scikit-learn
- Machine learning
- OpenCV
- I used the Django Rest Framework to create a multi tenant API with the aid of the django-tenant-schemas package.
- I used the Postgres Database as the persistence layer and specifically the PostgreSQL Schemas to ensure that all tenants using the API had their data.
- I used the REST architecture in designing my API.
- Researched existing digital solutions and prioritized key features for app release.
Qualifications
Education
University of Wolverhampton
Jul 2020 - Jun 2023
B.Sc (Hons) (Computer Science)
Courses
Reviews
Client Project Reviews
LD Talent
Created some very nice images through AI.
Interview Reviews
AudioPatternRanger
I absolutely would have hired you if I felt like my project belonged on this platform. Thank you for taking the time to discuss this project with me.