Henok T
The star rating is calculated by averaging the reviews provided by all clients the talent has worked with for a significant amount of time.
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.
Machine Learning Engineer Preferred Title
$20.00 /hr $ 30.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Average Response Time 12.0 hours
- Average Count of Messages/Day 0.4
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 30h PST, 72h 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 3.0/5
- Technical Breadth 4.0/5
- Algorithmic Thinking 4.0/5
- Technical Strength 4.0/5
- Teamwork 3.0/5
- Intellectual Merit 4.0/5
- Desktop Linux
- Phone Android
- Tablet Android Tablet
- Member Since Apr 16, 2021
- Profile Last Updated Sep 24, 2022
- Last Activity Sept. 24, 2022, 7:28 p.m. UTC
- Location Ethiopia
Profile Summary
A Machine Learning Engineer, with a software engineering background and experience building ML-powered solutions for different industries. Experience utilizing tools like Pandas, PySpark, Tensorflow, Pytorch, Scikit-learn, Plotly, Flask, Kubernetes, and CI/CD for end-to-end Computer Vision, NLP, and Geometric Deep Learning projects, including data preparation, processing, visual analytics, modeling, deployment, and maintenance.
Skills
Total Experience: 4 years
Tensorflow (3E, 3Y)
3 experiences, across 3 yearsPyTorch (2E, 2Y)
2 experiences, across 2 yearsComputer vision (1E, 2Y)
1 experience, across 2 yearsPython (1E, 2Y)
1 experience, across 2 yearsBlockchain API (1E, 1Y)
1 experience, 1 yearData Engineering (1E, 1Y)
1 experience, 1 yearWeb scrapers (1E, 1Y)
1 experience, 1 yearApache Kafka (1E, 1Y)
1 experience, 1 yearFlask (1E, 1Y)
1 experience, 1 yearMachine learning (1E, 1Y)
1 experience, 1 yearNumpy (1E, < 1Y)
1 experience, less than a yearJupyter (1E, < 1Y)
1 experience, less than a yearAWS (1E, < 1Y)
1 experience, less than a year
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 30h PST, 72h UTC
Day
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
06 - 18
06 - 18
06 - 18
06 - 18
06 - 18
06 - 18
PST
23 - 11
23 - 11
23 - 11
23 - 11
23 - 11
23 - 11
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
Software Engineer
Employment
Jun 2021 - Aug 2022
Sentiment Trading Company
Finance Industry
Project: Apollo18
- Apache Kafka
- Blockchain API
- Flask
- Web scrapers
- Data Engineering
- Machine learning
- Tensorflow
- Increased the company's data engineering systems efficiency by building and maintaining 10+ web scrapers that interact with various Blockchain APIs using Apache Airflow, Kubernetes, and Scrapy.
- Improved price forecasting Machine Learning model accuracy by 15% using a Deep Learning architecture.
- Successfully Implemented an Event-Driven System for handling high throughput trade orders with Apache Kafka (Faust) that reduced the amount of money lost on a trade.
- Built an ML-powered trading technical analysis tool using Tensorflow, Flask, Dash, and MongoDB that helps the trading team make profitable decisions.
Software Engineer
Internship
Mar 2019 - Jan 2021
iCog-Labs Company
Technology Industry
Project: All-in-one Facial Image Analysis
- Tensorflow
- PyTorch
- Python
- Computer vision
- Updated legacy Python codebases to add features and remove deprecated libraries.
- Developed Deep Learning models to extract insight from image data using PyTorch and Tensorflow.
- Built an in-house visualization tool for Computer Vision models.
Software Engineer
Employment
Nov 2020 - Jan 2021
Omdena Company
Technology Industry
Project: Improving Food Security in Senegal
- Numpy
- PyTorch
- Jupyter
- Tensorflow
- AWS
- Prepared datasets for image classification and segmentation projects utilizing AWS compute instances.
- Trained Computer Vision models for detecting plant disease using Jupyter, Numpy, and PyTorch.
- Resolved big data sharing issues and increased efficiency in the model-building process by utilizing MLOps tools.
- Built a Computer Vision model for segmenting agricultural land features using satellite imagery.
- Prepared a PyTorch and Tensorflow-based training Jupyter notebooks to help the team explore different models and parameters for two Computer Vision projects.
Qualifications
Education
Addis Ababa Science and Technology University
Oct 2015 - Jan 2021
B.Sc (Computer Engineering)
10 Academy
May 2022 - Aug 2022
Machine Learning Engineering and Data Engineering
Courses
Deep Learning Specialization
Mar 2019 - Oct 2019
DeepLearning.ai with Coursera
- Deep learning
- Computer vision
- Natural language processing
- Artificial intelligence
- Tensorflow