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Python
Computer Vision (CV)
Pandas
ML
AI
Keras
Matplotlib
NLTK
NumPy
Plotly
poetry
PyTorch
Scikit-learn
SciPy
Streamlit
TensorFlow
Google BigQuery
MySQL
Deep Learning
Keras
Kubeflow
Mlflow
NumPy
OpenCV
PyTorch
Scikit-learn
Spacy
TensorFlow
AWS RT
GCP Storage
Google BigQuery
CI/CD
Jenkins
Docker
Git
Payment Gateways
Regexp
Sublime Text
argparse
Custom API
Deep Learning (DL)
DVC
Hugging Face
Kubeflow for ML pipelines
Label Studio
MMCV
NLP
ONNX
Recommender Systems
tf-serving
Voxel51
YOLO
...

Data Science engineer with over 3 years of practical commercial experience in Natural Language Processing (NLP), Computer Vision (CV), and Recommender Systems. Available skills in data analysis using machine learning approaches to satisfy business needs, problem-solving, and other tasks in this sphere. A person, focused on obtaining the best results, using all knowledge and skills. Friendly and ready to help the team complete tasks and solve certain problems.

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Seniority Middle (3-5 years)
Location Ternopil, Ukraine
Python 3yr.
ML 2yr.
Node.js
Pandas
NumPy
Unreal Engine 1yr.
JavaScript
Django
Flask
Keras
Matplotlib
NLTK
Plotly
PyTorch
Scikit-learn
SciPy
TensorFlow
Logistic regression
Google BigQuery
MongoDB
MySQL
SQL
AWS ML (Amazon Machine learning services)
Deep Learning
Keras
OpenCV
PyTorch
Scikit-learn
Spacy
TensorFlow
AWS ML (Amazon Machine learning services)
AWS S3
Google BigQuery
Docker
Git
Kubernetes
3D Modelling
AI
Computer Vision
Computer Vision (CV)
Custom API
Deep Learning (DL)
GPT
NLP
Open3d
Prophet
Tensorboard
Trimesh
...

Certified Data Scientist bringing an 3+ year commercial expertise, particularly in NLP, CV, and 3D modeling, underpinned by a solid foundation in machine learning and data processing. Commands an advanced proficiency in Python, complemented by adeptness in JavaScript and NodeJS. Demonstrates in-depth experience with Python libraries such as Pandas, numpy, and PyTorch, and excels in deploying solutions with Git, Docker and API development. Proven track record in industries such as SEO and logistics, leveraging statistical models and ML solutions to drive data insights and optimization. Renowned for transforming complex requirements into scalable algorithms and models, with academic credentials in Mechanical and Computer Engineering.

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Seniority Middle (3-5 years)
Location Ternopil, Ukraine
Python
C#
C++
Keras
Matplotlib
NumPy
Pandas
PyTorch
Scikit-learn
Seaborn
TensorFlow
PostgreSQL
SQL
SQLite
AWS ML (Amazon Machine learning services)
Deep Learning
Keras
Machine Learning
NumPy
OpenCV
PyTorch
Scikit-learn
TensorFlow
Heroku
AWS Cloud Data Science services
AWS ML (Amazon Machine learning services)
Docker
FastApi
GitHub
GitLab
Linux
Microsoft Visual Studio
PyCharm
OOP
Data Science
DVC
LaTeX
MS VS Code
NLP
NLP/ML algorithms
speech and NLP/ML techniques
...

- 0.5 years of experience - Data Scientist with a Machine Learning background - Upper-Intermediate English.

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Seniority Junior (1-2 years)
Location Vinnitsa, Ukraine
Tableau
Microsoft Power BI
Python
VBA
VBA
SQL
AI Intro
Cleaning Data
Deep Learning
Neural Networks
GCP (Google Cloud Platform)
SAP
Shopify
...

- BI professional of waged experience in data analytics, predictive analysis, Google Analytics, Google Ads, Shopify and Omni Chanel Analysis. Experienced in Tableau, Power BI, SAP web intelligence, SQL and VBA. - Have strong conceptual understanding in Telecom, Retail, Banking, NBFI KPI Analysis, Data Visualization, Panel Data Analysis & Omni Marketing Data Analysis.

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Seniority Senior (5-10 years)
Location Bangladesh
Tableau 5yr.
Qlik Sense 2yr.
Python
ETL
Microsoft Power BI
SQL
Deep Learning
Excel
Looker Studio
Natural Language Processing
...

- 5 years of experience in developing and maintaining complex Tableau dashboards and reports using multiple data sources for diverse industries - 2 years of experience with Qlik; led the design and development of interactive dashboards using Qlik Sense, Power BI, and Tableau; designed and implemented data models in Qlik Sense, facilitating data discovery and exploration. - Upper-Intermediate English

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Seniority Senior (5-10 years)
Location Rawalpindi, Pakistan
Machine Learning Algorithms 6yr.
Python 6yr.
NLP 6yr.
SQL 6yr.
Machine Learning Frameworks 6yr.
Deep Learning 5yr.
Keras 4yr.
Keras 4yr.
Signal processing 3yr.
PyTorch 2yr.
PyTorch 2yr.
R 1yr.
PySpark 1yr.
Beautiful Soup
Flask
Matplotlib
NLTK
NumPy
Pandas
Plotly
Scikit-learn
SciPy
Seaborn
TensorFlow
D3.js
Shiny
NumPy
Scikit-learn
Spacy
TensorFlow
Azure
GCP (Google Cloud Platform)
Azure
Agile
Scrum
BitBucket
Git
SourceTree
Jira
RESTful API
Anomaly detection
Data Analytics
Data Visualization Tools
Gensim
Predictive Analytics
Statistical modeling
Statsmodels
Superset
Time series analysis
...

- About 6 years of experience in Data Engineering - Upper-Intermediate English. - Available ASAP.

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Seniority Senior (5-10 years)
Location India
Java 15yr.
Python 3yr.
Hadoop ecosystem
Scala
Hibernate/JPA
JavaFX
Spring
Spring Data
Spring Integration
Spring JDBC
Spring model-view-controller (MVC) framework
Swing
Vaadin
Mockito
NLTK
PyTorch
Apache Hive
Apache Oozie
Apache Spark
Apache Spark ML
AWS Athena
Apache Hive
Apache Spark
Apache Spark ML
AWS ElasticSearch
Cassandra
HDFS
HDP
Hibernate/JPA
MariaDB
MongoDB
MySQL
PostgreSQL
Apache Spark ML
Deep Learning
Machine Learning
PyTorch
AWS
GCP (Google Cloud Platform)
AWS API Gateway
AWS Cloudformation
AWS EC2
AWS ElasticSearch
AWS EMR
AWS Lambda
AWS RDS (Amazon Relational Database Service)
AWS S3
AWS SNS
AWS SQS
Agile
Scrum
TDD
Waterfall
Ansible
Bamboo
Gradle
Jenkins
Kubernetes
OpenVPN
Apache Maven
JMeter
JUnit
Mockito
Apache Oozie
Kafka
AWS API Gateway
BIND
Kerberos
LDAP
OpenVPN
Camunda
Eclipse
Nginx
OpenVPN
Terraform
CUDA
FairSeq
FindBugs
Grid Computing
JetBrains IntelliJ IDEA
JMH
KeyCloack
MPI
Natural Language Processing
Network technologies
OpenCL
OpenMP
PMD
Ranger
Raspberry PI
Spark MLLib
Spark Standalone cluster
Spring Boot
Stanford Core NLP
virtualization
...

• 10+ year experience with JAVA and Linux operating systems: Java 11, Spring Boot, Spring Data JPA, MySQL/MongoDB, ElasticSearch, Jenkins CI • Big Data, Data Engineering, NLP, Corpus Linguistics, ML, DL • Design and implement a distributed warehouse system (AWS migration), REST API design and cache implementation (1,000-10,000 requests/sec), Design and implement high-load microservices • Deliver special courses devoted to concurrency and prepared handbook on “Parallel and Distributed Computations” [technologies: (basics of OpenMP, MPI, CUDA, OpenCL), advanced in Java concurrency]; • Scientific projects at university related research increasing effectiveness of crypto-analysis • Upper-Intermediate English • Available Full-time • Ready to start in 2 weeks • No scheduled vacations within next 3months

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Seniority Senior (5-10 years)
Location Ternopil, Ukraine

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Want to hire Deep Learning developer? Then you should know!

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How and where is Deep Learning used?

  • Medical Imaging: Diagnosing diseases
  • Autonomous Vehicles: Self-driving cars
  • Natural Language Processing: Language translation
  • Fraud Detection: Identifying fraudulent activities
  • Recommendation Systems: Personalized recommendations
  • Robotics: Autonomous robots
  • Computer Vision: Object recognition
  • Speech Recognition: Voice-controlled assistants
  • Financial Forecasting: Predicting market trends
  • Gaming: Enhancing player experiences

Compare Junior, Middle, Senior, and Expert/Team Lead Deep Learning Developer roles

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior0-2 years
  • Assist in model development
  • Data preprocessing
  • Basic troubleshooting
$60,000
Middle2-4 years
  • Model optimization
  • Implementing algorithms
  • Collaborate with team members
$80,000
Senior4-6 years
  • Lead project development
  • Research new technologies
  • Mentor junior developers
$100,000
Expert/Team Lead6+ years
  • Architect complex solutions
  • Set technical direction
  • Manage team projects
$120,000

Quick Facts about Deep Learning.

  • Deep learning emerged in 1986 as a method of machine learning.
  • Popular projects involving deep learning are image recognition and natural language processing.
  • Entry into deep learning requires a solid understanding of linear algebra and calculus.
  • Convolutional Neural Networks (CNNs) are among the most popular related technologies to deep learning.
  • In 1997, IBM’s Deep Blue became the first computer chess-playing system to defeat a reigning world chess champion, Garry Kasparov.

TOP Deep Learning Related Technologies

  1. TensorFlow (Google)
  2. PyTorch (Facebook)
  3. Keras (Francois Chollet, 2015)
  4. Caffe (Berkeley AI Research)
  5. MXNet (Apache)

What are top Deep Learning instruments and tools?

  • TensorFlow: Created by Google. Released in 2015.
  • PyTorch: Developed by Facebook. Released in 2016.
  • Keras: An API designed for TensorFlow. Released in 2015.
  • Caffe: Developed by Berkeley AI Research. Released in 2014.
  • Theano: Developed by the Montreal Institute for Learning Algorithms. Released in 2007.
  • MXNet: Apache Software Foundation project. Released in 2015.
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Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
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FAQs on Deep Learning Development

What is a Deep Learning Developer? Arrow

A Deep Learning Developer is a specialist in the Deep Learning framework/language, focusing on developing applications or systems that require expertise in this particular technology.

Why should I hire a Deep Learning Developer through Upstaff.com? Arrow

Hiring through Upstaff.com gives you access to a curated pool of pre-screened Deep Learning Developers, ensuring you find the right talent quickly and efficiently.

How do I know if a Deep Learning Developer is right for my project? Arrow

If your project involves developing applications or systems that rely heavily on Deep Learning, then hiring a Deep Learning Developer would be essential.

How does the hiring process work on Upstaff.com? Arrow

Post Your Job: Provide details about your project.
Review Candidates: Access profiles of qualified Deep Learning Developers.
Interview: Evaluate candidates through interviews.
Hire: Choose the best fit for your project.

What is the cost of hiring a Deep Learning Developer? Arrow

The cost depends on factors like experience and project scope, but Upstaff.com offers competitive rates and flexible pricing options.

Can I hire Deep Learning Developers on a part-time or project-based basis? Arrow

Yes, Upstaff.com allows you to hire Deep Learning Developers on both a part-time and project-based basis, depending on your needs.

What are the qualifications of Deep Learning Developers on Upstaff.com? Arrow

All developers undergo a strict vetting process to ensure they meet our high standards of expertise and professionalism.

How do I manage a Deep Learning Developer once hired? Arrow

Upstaff.com offers tools and resources to help you manage your developer effectively, including communication platforms and project tracking tools.

What support does Upstaff.com offer during the hiring process? Arrow

Upstaff.com provides ongoing support, including help with onboarding, and expert advice to ensure you make the right hire.

Can I replace a Deep Learning Developer if they are not meeting expectations? Arrow

Yes, Upstaff.com allows you to replace a developer if they are not meeting your expectations, ensuring you get the right fit for your project.