Prajin K
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If such data is not available, the star rating is calculated from the fraction of work sessions approved by their past clients versus the total tracked by the talent.
If such data is not available, the star rating defaults to the interview rating of the talent at the time of the vetting process.
Other data including reviews from interviews are available on the talents’ profiles but do not influence their star rating, though they do influence their position in the search results.
If such data is not available, the star rating is calculated from the fraction of work sessions approved by their past clients versus the total tracked by the talent.
If such data is not available, the star rating defaults to the interview rating of the talent at the time of the vetting process.
Other data including reviews from interviews are available on the talents’ profiles but do not influence their star rating, though they do influence their position in the search results.
ML ENGINEER Preferred Title
$31.25 /hr $ 24.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Average Response Time 12.0 hours
- Average Count of Messages/Day 0.2
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 28h PST, 47h UTC
- Code Quality 60%
- Soft Skill Attributes 60%
- Expertise 2/3
- Coding Challenges 60%
- No. of Lifelong Learning Projects 2
- No. of Coding Challenges Completed 2 More details
- Software Engineering Process 4.0/5
- Technical Breadth 4.0/5
- Algorithmic Thinking 4.0/5
- Technical Strength 4.0/5
- Teamwork 3.0/5
- Intellectual Merit 4.0/5
- English Communication 4.0/5
- Desktop Mac
- Phone iPhone
- Tablet iPad
- Member Since Apr 18, 2022
- Profile Last Updated Apr 11, 2022
- Last Activity Aug. 27, 2022, 4:53 p.m. UTC
- Location Nepal
Profile Summary
I am a Computer Science graduate, and working professionally as an AI Engineer with core focus on building and integrating Machine learning applications.
Skills
Total Experience: 3+ years
PyTorch (5E, 3Y)
5 experiences, across 3 yearsPython (5E, 3Y)
5 experiences, across 3 yearsDeep learning (4E, 2Y)
4 experiences, across 2 yearsNatural language processing (2E, 2Y)
2 experiences, across 2 yearsDocker (3E, 2Y)
3 experiences, across 2 yearsSpeech recognition (1E, 1Y)
1 experience, 1 yearComputer vision (1E, 1Y)
1 experience, 1 yearAzure (1E, 1Y)
1 experience, 1 yearAWS Lambda (1E, 1Y)
1 experience, 1 yearAWS Elasticsearch (1E, 1Y)
1 experience, 1 yearAWS (1E, 1Y)
1 experience, 1 yearKubernetes (1E, 1Y)
1 experience, 1 yearFlask (1E, 1Y)
1 experience, 1 yearMachine learning (1E, < 1Y)
1 experience, less than a yearPandas (1E, < 1Y)
1 experience, less than a year
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 28h PST, 47h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
05 - 17
12 - 17
12 - 17
12 - 17
12 - 17
12 - 17
05 - 17
PST
22 - 10
05 - 10
05 - 10
05 - 10
05 - 10
05 - 10
22 - 10
Vetting
- Interview Data
- Agile Development Process
- Productivity and Responsiveness
- Teamwork
- Software Engineering
- Logical Thinking
- Technical Strength
- Intellectual Merit
- English Communication
- Documentation
- System Design
- Coding Challenges60%
- Algorithms Score60%
- General Score60%
- Easy Algorithm
- Correctness60%
- Performance60%
- Medium Algorithm
- Correctness60%
- Performance60%
- Hard Algorithm
- Correctness60%
- Performance60%
- Expertise2/3
- Design Patterns and Architectures2/3
- Debugging2/3
- Stack Traces2/3
- Testing2/3
- System Administration2/3
- Soft Skill Attributes60%
- Entrepreneurial60%
- Whole Brained60%
- Divergent Thinking / Creativity60%
- Design Ability60%
- Empathy60%
- Project Management Ability60%
- Security60%
- Code Quality60%
- Complex Logic60%
- Models60%
- Controllers60%
- Templates60%
- APIs60%
- Training/Testing Data Models60%
- Code Readability60%
- Ongoing Evaluation
- Number of Lifelong Learning Project2
- Number of Coding Challenge Completed3
Experience
AI Engineer
Employment
Jan 2022 - Present
Dogma Group Company
Technology Industry
Project: Contrastive Learning from image and text
- Deep learning
- Computer vision
- Azure
- PyTorch
- Python
- Worked on computer vision techniques: Object detection, Instance segmentation ( training and fine tuning ) in Python and Pytorch. Involved in hiring ML human resources ( Interview, Onboarding )
- Research on deep learning approach such as Contrastive learning techniques to extract information from images and text at once. Deployed demo app in Azure.
ML Engineer
Course Project
Sep 2021 - Present
Tribhuwan University Company
Research Industry
Project: Nepali Automatic Speech Recognition System
- Natural language processing
- Deep learning
- Speech recognition
- PyTorch
- Python
- Nepali Automatic Speech recognition system.
- Worked on Data collection, validation, Model building in Pytorch and deployment.
- Worked on Supervised learning ( RNN, Transformers ) with Python.
- Worked on Semi Supervised learning deep learning methods, i.e., on wav2vec2 architecture (training , fine-tuning the model ).
- Worked on Natural Language processing pipeline.
Machine Learning Engineer
Employment
Feb 2021 - Dec 2021
Fusemachines Company
Technology Industry
Project: Plagiarism Checker
- Natural language processing
- Deep learning
- Docker
- AWS Elasticsearch
- AWS Lambda
- Python
- PyTorch
- Developed Plagiarism checker (English and Nepali ) in Python.
- Used AWS Elasticsearch for finding syntactically similar documents, deep learning methods built with Pytorch to compare them semantically.
- Worked on Natural language processing pipeline.
- Deployed the containerized application( Docker ) on AWS lambda with CI/CD pipeline ( Jenkins).
Machine Learning Engineer
Employment
Apr 2020 - Jan 2021
Fusemachines Company
Technology Industry
Project: Digitzing Online Examination
- Docker
- PyTorch
- Python
- Kubernetes
- Flask
- AWS
- Developed Face Detection, Recognition, Anti-spoofing application using Pytorch and Python.
- Deployed the containerized micro-services with event driven architecture using AWS SQS, ECR, and EKS. (Kubernetes).
- Developed Gaze estimation, head-pose estimation models.
- Developed Speaker verification using Python and Pytorch. Used AWS services S3, and SQS
- Deployed the containerized micro-services ( Docker) in Flask.
Machine Learning Engineer Trainee
Employment
Dec 2019 - Mar 2020
Fusemachines Company
Technology Industry
Project: Content Creation
- Deep learning
- Docker
- Pandas
- PyTorch
- Machine learning
- Python
- Involved heavily in creating content (Reading materials, Slides, Videos, Coding Assignments, Projects) related to Machine learning, Deep learning using Python, and Pytorch.
- I learned in-depth about ML, DL algorithms, use cases, data analysis with Pandas, and deployment pipeline with Docker. This experience improved my Python proficiency.
Qualifications
Education
Bhaktapur Multiple Campus
Aug 2018 - Aug 2022
BSC. CSIT (Computer Science)
Courses
AWS Machine Learning Speciality
Jul 2021 - Aug 2022
Amazon Web Service
- Deep learning
- Docker
- AWS S3
- AWS ECR
- AWS EC2
- Machine learning
- AWS
Microsoft Certified: Azure Data Scientist Associate
Aug 2020 - Sep 2020
Microsoft Azure
- Deep learning
- Azure
- Data mining
- Data Engineering
- Machine learning