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Suresh

Suresh

PyTorch Developer

Experience6 years
AvailabilityFull-time

Suresh has 6 years of experience with deep expertise in machine learning and deep learning. He has a track record of solving business-related problems in the finanace, banking, retail, healthcare and HR industries. He is highly skilled in data engineering, Python, PySpark, SQL, Scikit-Learn, etc.

Expert in
  • PySpark
  • Python
  • SQL
  • Deep learning
  • PyTorch
Also worked with
  • Apache Spark Hadoop
  • Keras
  • ML
Hoang

Hoang

PyTorch Developer

Experience3 years
AvailabilityFull-time

Hoang is an AI/ML/SWE enthusiast who has 3+ years of experience working in startups and large corporations. He has performed AI/ML roles at Microsoft, SoftBank, and Fujitsu.

Expert in
  • HTML
  • PyTorch
  • A/B Testing
  • Git
  • Flask
Also worked with
  • Java
  • Neo4j
  • JavaScript
  • Python
  • SQL
Ogban

Ogban

PyTorch Developer

Experience5 years
AvailabilityFull-time

Ogban has 5+ years implementing a wide range of machine learning and deep learning models. His strongest skills include working with python for machine learning including the major deep learning libraries (Pytorch, Tensorflow etc.).

Expert in
  • PyTorch
  • Deep Learning
  • Python
  • SQL
  • PostgreSQL
Also worked with
  • Python for Data Science
  • GitHub
  • Django Rest Framework
  • Data Science
Hameer

Hameer

PyTorch Developer

Experience6 years
AvailabilityFull-time

Hameer is a software developer having 6 years of experience. He is proficient in several programming languages and capable of learning new technologies at a very fast pace.

Expert in
  • PyTorch
  • Numpy
  • Python
  • Communication
  • MATLAB
Also worked with
  • Git
  • C++
  • Data Engineering
  • Latex
Chao

Chao

PyTorch Developer

Experience6 years
AvailabilityFull-time

Chao is a software developer with 6 years of comprehensive experience in developing machine learning models, back-end development based on Django/Flask, front-end development based on Nodejs/React.js, UI-based applications, and the zeal to work, learn, and grow.

Expert in
  • PyTorch
  • NumPy
  • OpenCV
  • C#
  • Linux
Also worked with
  • Java
  • Scipy
  • Python
  • HTTP
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How to hire PyTorch developers? Skills to look for, interview questions, and more.

PyTorch is a machine learning library for Python used mainly for natural language processing. This open-source software is one of the latest deep learning frameworks and is gaining popularity for its simplicity, ease of use, dynamic computational graph, and efficient memory usage. Due to these multitasking features, the demand to hire PyTorch developers is increasing rapidly among organizations.

Though finding a good PyTorch developer is not easy, some basic knowledge and professional tips can ease hiring. With that, we're here to assist all recruiters who are looking to hire PyTorch developers by themselves. Hiring a PyTorch developer requires a fair amount of software development expertise in general. However, if you're a non-technical manager interested in learning more about the hiring process of a PyTorch developer, we've put up an excellent resource for you.

Skills to look for in a PyTorch developer

At a senior level, PyTorch developers should have the following skills in their arsenal:

1. High-level proficiency in core Python

As a library based on the Python programming language, it is crucial to know whether the developer is well-versed with core Python concepts. While hiring, you should consider candidates with a solid knowledge of various basic concepts such as variables & data types, exception handling, file handling, data structure, and object-oriented programming. It is quite an obvious skill for senior developers, but you should always double-check from your end.

2. High proficiency in applied mathematics

Math is a vital skill for machine learning engineers. It is also one of the fundamental elementary school subjects with a wide range of machine learning applications. As an ML-based library, PyTorch developers ought to have an excellent mathematical aptitude to employ a variety of mathematical formulas in choosing the best method for a given set of data. They can also use arithmetic to define parameters and estimate confidence levels. Several algorithms developed from statistical modeling processes are straightforward and simple to comprehend if one has a strong mathematical background. Some of the important topics you need to test the developer include linear algebra, probability, statistics, multivariate calculus, distributions, etc.

3. Understanding of Neural networks

Neural networks make up a significant part of the deep learning process and are inspired by the structure of the human brain. They are complex structures created from artificial neurons and can process multiple inputs and produce a singular output. Understanding this architecture with a knowledge of its core fundamentals is essential for PyTorch developers and a skill to test for while considering candidates for hire.

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4. Experience with Natural Language Processing (NLP)

Natural Language Processing is built on the foundation of several diverse libraries. These libraries contain a number of functions that can be used to help computers understand natural language by breaking the text down into grammar, extracting key phrases, and deleting unnecessary words, among other things. The PyTorch developer ought to be familiar with some of these libraries like the Natural Language Toolkit, which is the most popular platform for creating applications related to NLP.

5. Expertise in computer vision

Computer vision involves training computers to understand and interpret the visual world. This includes accurately identifying and locating objects, then reacting to what they see through the use of digital images from deep learning models, videos, and cameras. A developer who has a good understanding of computer vision can easily identify, solve problems and achieve better and optimized results.

6. Excellent skills in communication, collaboration, and critical thinking

It is also essential to have soft skills that complement technical knowledge. PyTorch developers need to be capable of accurately and clearly communicating ideas across the business, using the correct tone and body language. They will also utilize their skills to manage teams where necessary, as well as work closely with other teams across the organization to run and implement projects while developing innovative ideas to solve complex business problems with logic and reasoning. Therefore, ensure to hire a talented PyTorch developer who is skilled enough to perform various business functions while leveraging these skills and competencies.

Create a hiring funnel

Creating a hiring funnel will provide you with numerous benefits, like assisting you in identifying the top skills and recruiting a PyTorch developer who will fit into your company's culture.

What Turing does for you

Candidates screening
Candidates screening

We will help you select the best talents and hire a PyTorch developer who will fit in your company culturally.

Test task
Test task

We verify if the candidate really wants to work at your company and is able to spend 5+ hours to prove it by rigorous tests. It helps us to see a developer's caliber.

Technical test
Technical test

Developers are asked Python related questions and made to solve tricky problems. We use open questions. The goal is not only to test developers’ knowledge – we also want to find out their way of thinking.

Giving specific feedback
Giving specific feedback

We provide explicit feedback on both the test task and the technical test after we have checked the developer's expertise.

What you do

Interview
Interview

You can interview the shortlisted developers to check if the candidate matches your requirements and is a good fit for your company.

Hired/Not-hired
Hired/Not-hired

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Top interview questions to hire PyTorch developers.

Whether you're an IT recruiter or a project manager, you are aware that finding the best developers is vital to the success of your project. Here are some sample interview questions to use when looking for a new PyTorch developer.

By asking about the significance, you can find out how much the developer knows about the basics. The features of PyTorch are as follows:

  • Easy interface:
    PyTorch offers a smooth and easy-to-use API. It is straightforward to operate and runs on Python.
  • Computational Graphs:
    PyTorch provides an excellent platform for dynamic computational graphs so that a user can change them during runtime. This is more useful when a developer has no idea of how much memory is required for creating a neural network model.
  • Imperative Programming:
    PyTorch performs computations through each line of the written code. This is similar to Python program execution.

You can use this question to find out if the candidate is knowledgeable in the core concepts of the library. He/She may answer that a Tensor is a multi-dimensional matrix containing elements of a single data type. They play an important role in deep learning with PyTorch. Tensors in PyTorch are the same as the NumPy array. It manually computes the forward pass, loss, and backward pass. The most significant difference between the PyTorch Tensors and NumPy array is that Pytorch can run either in CPU or GPU. A tensor is treated as a generalized matrix. It could be a 1D tensor (vector), 2D tensor(matrix), 3D tensor(cube) or 4D tensor(cube vector).

The Autograd module is an automatic differentiation technique used in PyTorch. It is more powerful when building a neural network. There is a recorder that records each performed operation and then it replays it backs to compute the gradient. If the candidate knows this, he/she has a good understanding of terminologies in PyTorch.

Each torch.Tensor has a torch.device, torch.layout, and torch.dtype. The torch.dtype defines the data type, torch.device represents the device on which a torch.Tensor is allocated, and torch.layout represents the memory layout of a torch.Tensor. The candidate’s technical competency can be shown with this answer.

The deep neural network is a kind of neural network with many layers. "Deep" means that the neural network has a lot of layers that look like a deep stack of layers within the network. The convolutional neural network is another kind of deep neural network. The Convolutional Neural Network has a convolution layer, that uses filters to convolve an area in input data into a smaller area, detecting important or specific parts within the area. The convolution can be used on the image as well as text. The developer’s ability to give a satisfactory answer to this question demonstrates a high-level proficiency.

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More interview questions to hire PyTorch developers.

  • What are the essential elements of PyTorch?
  • How can one get derivatives of the function in PyTorch?
  • What is the difference between Tensorflow and PyTorch?
  • What is the optim module in PyTorch?
  • Differentiate between torch.nn and torch.nn.functional?

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Turing offers top-quality, cost-effective, and highly productive PyTorch developers who belong to the top 1% of the world's remote developers. All Turing PyTorch developers are selected only after going through a series of rigorous tests where their skills are evaluated for a Silicon Valley bar. Daily standups are mandatory for every Turing developer as they keep the developer and the customer in alignment with the discussed goal. All Turing remote PyTorch developers work for at least 4 hours in your time zone for your convenience.

Turing has created the first and only Intelligent Talent Cloud to vet remote developers for a Silicon Valley bar. Turing tests developers based upon actual skills vs. self-reported experience from traditional resumes or job interviews. Every developer at Turing has to clear our tests for programming languages, data structures, algorithms, system designs, software specialization, frameworks, and more. Each Turing developer goes through our automated seniority assessment test comprising 57 calibrated questions in 5 areas — project impact, engineering excellence, communication, people, and direction.

With Turing, you can hire the best remote developers for 100+ skills such as React, Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, DevOps, Machine Learning, etc. Turing also offers developers based on tech stack and seniority.

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