PyTorch Developer

A PyTorch Developer specializes in developing machine learning models and applications using the PyTorch framework, leveraging deep learning algorithms for various domains and use cases.
Salary Insights
High-ROI Certifications
Potential Lateral Jobs
Publications/ Groups

PyTorch Developer

Market
National (USA)
Base Salary
$ / year
Satisfaction
Additional Benefits
Yes
Industry
All
Education
Bachelor's Degree

The average salary for PyTorch Developer is $ / year according to .com

There are no updated reports for PyTorch Developer salaries. You can check potential lateral job opportunities in this information stack to find related salary information.

PyTorch Developer role may have an alternate title depending on the company. To find more information, you can check .com.

Career Information

As a PyTorch Developer, you will be responsible for designing and developing machine learning models using the PyTorch framework. You will need strong programming skills, as well as a deep understanding of machine learning principles and algorithms. Strong problem-solving and analytical skills are also important, as you will be responsible for training and optimizing models for various applications.

The average salary for PyTorch Developer is $ / year according to .com
AI Disclaimer
The following text about the Job role of PyTorch Developer has been generated by an AI model developed by OpenAI. While efforts have been made to ensure the accuracy and coherence of the content, there is a possibility that the model may produce hallucinated or incorrect information. Therefore, we strongly recommend independently verifying any information provided in this text before making any decisions or taking any actions based on it.

A PyTorch Developer is a software engineer who specializes in developing applications using the PyTorch open source machine learning library. PyTorch is a powerful library for deep learning and artificial intelligence, and is used by many companies to develop applications for a variety of tasks.

The most important skills for a PyTorch Developer include a strong understanding of machine learning and deep learning concepts, as well as a good understanding of the PyTorch library. They should also have experience with Python programming and be familiar with other libraries such as NumPy and SciPy. Additionally, they should have a good understanding of the underlying mathematics and algorithms used in machine learning.

The primary tasks of a PyTorch Developer include developing applications using the PyTorch library, creating models and algorithms for machine learning tasks, and optimizing existing models and algorithms. They should also be able to debug and troubleshoot any issues that arise during development. Additionally, they should be able to deploy applications to production and maintain them.

In addition to the technical skills, PyTorch Developers should also have strong communication and collaboration skills. They should be able to work with other developers and stakeholders to ensure that the applications they develop meet the requirements of the project. They should also be able to explain their work to non-technical stakeholders.

Overall, PyTorch Developers are highly skilled software engineers who specialize in developing applications using the PyTorch library. They should have a strong understanding of machine learning and deep learning concepts, as well as a good understanding of the PyTorch library. They should also have experience with Python programming and be familiar with other libraries such as NumPy and SciPy. Additionally, they should have strong communication and collaboration skills.

Potential Lateral Jobs
Explore the wide range of potential lateral job opportunities and career paths that are available in this role.

High-ROI Programs

Most roles require at least a bachelor's degree. To remain competitive, job seekers should consider specialization or skill-specific programs such as specialization, bootcamps or certifications.
Certification Programs
Consider pursuing specialized certifications or vendor-specific programs to enhance your qualifications and stand out in the job market.

AWS Certified Machine Learning — Specialty Certification

MLS-C01

The AWS Certified Machine Learning - Specialty certification covers a wide range of topics, including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations on the AWS Cloud. 

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Google Certified Professional Machine Learning Engineer

The Google Machine Learning Certification is a high-ROI program designed for ML engineers who want to gain specialized machine learning skills using Google Cloud technologies.

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Databricks Certified Data Engineer Associate

The Databricks Data Engineer Certification program is highly sought after, designed to evaluate an individual's proficiency in utilizing the Databricks Lakehouse Platform for performing fundamental data engineering tasks.

Intermediate
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AWS Certified Data Analytics — Specialty

DAS-C01

The AWS Data Analytics Certification program validates a deep understanding of AWS data analytics services and their integration with each other to derive insights from data, making it suitable for individuals pursuing a role focused on data analytics.

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CKAD: Certified Kubernetes Application Developer

CKAD

The Certified Kubernetes Application Developer (CKAD) program validates a developer's skills in designing and developing applications in Kubernetes.

Intermediate
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Microsoft Certified: Azure AI Engineer Associate

AI-102

The Azure AI Certification is a high-ROI program designed for professionals who are passionate about building, managing, and deploying AI solutions using Azure Cognitive Services and Azure services.

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Microsoft Certified: Azure Data Scientist Associate

DP-100

The Microsoft Certified: Azure Data Scientist Associate is a high-ROI program designed for professionals who have expertise in applying data science and machine learning techniques to implement and manage machine learning workloads on Azure.

Intermediate
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Specialty Courses improving
If you want to improve your skills and knowledge in a particular field, you should think about enrolling in a Nanodegree or specialization program. This can greatly improve your chances of finding a job and make you more competitive in the job market.

Intro to Machine Learning with PyTorch

Nanodegree

This high-quality Nanodegree program teaches foundational machine learning techniques, from data manipulation to unsupervised and supervised algorithms.

Intermediate
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Machine Learning Specialization

Specialization

Master fundamental AI concepts and practical machine learning skills through this high-ROI specialization taught by AI visionary Andrew Ng.

Machine Learning with PySpark

Course

This program enhances your skills in data-driven predictions using Apache Spark, covering techniques like decision trees, logistic and linear regression, ensembles, and pipelines.

Intermediate
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Machine Learning Scientist with Python

Career Track

Master key machine learning skills with 23 concise courses on Python, supervised & unsupervised learning, NLP, TensorFlow, PyTorch, Keras, and more for a successful career.

Intermediate
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Machine Learning Engineering for Production (MLOps) Specialization

Specialization

This MLOps Specialization offers an in-depth understanding of creating, deploying, and maintaining integrated systems, managing data changes, and optimizing performance.

Practicing Machine Learning Interview Questions in Python

Practice

Linear Algebra for Machine Learning and Data Science

Specialization

This intermediate-level course will enhance your understanding of vector and matrix algebra, linear transformations, and eigenvalues, enabling you to apply these concepts to machine learning problems effectively.

Become a Machine Learning Engineer for Microsoft Azure

Nanodegree

This Nanodegree program strengthens learners' skills in building and deploying ML solutions using open-source tools and frameworks, providing exposure to Azure Machine Learning's MLOps capabilities for end-to-end ML lifecycle management.

Intermediate
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AWS Machine Learning Engineer

Nanodegree

In this Nanodegree program, you'll gain hands-on experience in building, training, and deploying machine learning models using Amazon SageMaker.

Intermediate
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Improving your Statistical Inferences

Course

This course enhances students' statistical inference skills in empirical research through likelihood functions, Bayesian statistics, P-values, and high statistical power, with online instruction in essential concepts and proficiency in equivalence testing.

Intermediate
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Probabilistic Graphical Models

Specialization

This specialization boosts critical reasoning via lectures, quizzes, and tasks on probabilistic graphical models (PGMs), focusing on representation, inference, and learning for profound comprehension of machine learning problem formulation.

Business Statistics and Analysis Specialization

Specialization

This online Specialization equips you with essential business data analysis tools and statistical skills for advanced data science, culminating in a Capstone project to inform business decisions.

Intermediate
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Probability Theory: Foundation for Data Science

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This comprehensive course for beginners teaches probability calculation, outcome types, conditional events, random variables, and data collection, preparing students for Data Science careers with essential knowledge in key theories.

Intermediate
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Statistics Foundations: Understanding Probability and Distributions

Course

The foundation course provides essential skills for advanced topics, including set theory, introductory probability, statistical research, distribution measures, covariance, correlation, statistical distributions, random variables, probability density functions, and moment-generating functions.

Probability and Statistics: To p or not to p?

Course

This course provides a comprehensive understanding of statistical tools for informed decision-making, covering basics with clear examples, interval estimation, hypothesis testing, and multivariate applications, ensuring a strong grasp of probability and descriptive statistics.

Resource Stacks

We are soon crowdsourcing these resource stacks to collate the best resources, such as publications, community groups, job boards, etc., that are practically suitable for every contextual stack.
Publications
Discover the wide array of publications that professionals in this role actively engage with, expanding their knowledge and staying informed about the latest industry trends and developments.
Communities updating
Discover the thriving communities where professionals in this role come together to exchange knowledge, foster collaboration, and stay at the forefront of industry trends.
Research updating
We are currently in the process of updating contextual resources and we will be adding the new ones to the list shortly.
AI Disclosure: We are testing AI technologies to ensure the accuracy and coherence of recommendations. However, it is important to note that there is a possibility that the model may create hallucinated or incorrect inferences. Therefore, we highly recommend independently verifying any information provided in these stacks before making any decisions or taking any actions based on it.
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