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Deep Learning

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Deep Learning
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Hire Deep Learning Developers and Engineers

Viktoria T., Deep Learning Developer

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.

Deep Learning

Deep Learning

Python

Python

Computer Vision (CV)

Computer Vision (CV)

Pandas

Pandas

ML

ML

AI

AI

Taras S., Deep Learning Developer

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.

Deep Learning

Deep Learning

Python

Python   3 yr.

Node.js

Node.js

Pandas

Pandas

NumPy

NumPy

ML

ML   2.5 yr.

Nazar P., Deep Learning Developer

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

Deep Learning

Deep Learning   0.5 yr.

Python

Python   0.5 yr.

Munshi M., Deep Learning Developer

- 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.

Deep Learning

Deep Learning

Tableau

Tableau

Microsoft Power BI

Microsoft Power BI

Mohsin T., Deep Learning Developer

- 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

Deep Learning

Deep Learning

Tableau

Tableau   5 yr.

Qlik Sense

Qlik Sense   2 yr.

Krishna N., Deep Learning Developer

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

Deep Learning

Deep Learning   5 yr.

Machine Learning Algorithms

Machine Learning Algorithms   6 yr.

Python

Python   6 yr.

NLP

NLP   6 yr.

Andriy L., Deep Learning Developer

$30/hr

• 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

Deep Learning

Deep Learning

Java

Java   15 yr.

Hadoop ecosystem

Hadoop ecosystem

Python

Python   3 yr.

Gilbert A., Software engineering with Deep Learning, Python

Gilbert A., Deep Learning Developer

- Experienced data scientist with 5+ years of experience in data science, analytics & software engineering - Deploying and Hosting a Machine Learning Model Using Flask, Heroku and Gunicorn - Transfer Learning with PyTorch - Intermediate English - Available ASAP

Deep Learning

Deep Learning

Python

Python   5 yr.

Mun I., Data/Business Analyst with Deep Learning, Tableau, SQL

Mun I., Deep Learning Developer

- Data/Business Analyst professional with 5+ years 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. - Upper-Intermediate English. - Available ASAP.

Deep Learning

Deep Learning

Tableau

Tableau

SQL

SQL

Muyide I., Senior Python Engineer with Deep Learning, Python

Muyide I., Deep Learning Developer

- 9+ years of experience in IT - Python: 5/6 years - Django: 5 years - Ready to work in CST timezone - Start date: 2 weeks After the Offer has been made. But if there is a reason to start earlier, I should be able to work around that. - Upper-Intermediate English

Deep Learning

Deep Learning

Python

Python   6 yr.

Only 3 Steps to Hire Deep Learning Developer

1
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Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
2
Meet Carefully Matched Deep Learning Talents
Within 1-3 days, we’ll share profiles and connect you with the right Deep Learning talents for your project. Schedule a call to meet engineers in person.
3
Validate Your Choice
Bring new Deep Learning expert on board with a trial period to confirm you hire the right one. There are no termination fees or hidden costs.

Welcome on Upstaff: The best site to hire Deep Learning Developer

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Upstaff.com was launched in 2019, addressing software service companies, startups and ISVs, increasingly varying and evolving needs for qualified software engineers

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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.

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Table of Contents

How and where is Deep Learning used?

How and where
  • 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.

Facts about
  • 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

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?

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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