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Pytorch Phd Jobs (NOW HIRING)

Motional

Machine Learning Systems Engineer

Las Vegas, NV · On-site +1

... PhD in Computer Science, Computer Engineering, or a related technical discipline. * Software Engineering : Strong proficiency in Python. * ML Frameworks : Extensive hands-on experience with PyTorch.

Motional

Machine Learning Systems Engineer

Boston, MA · On-site +1

... PhD in Computer Science, Computer Engineering, or a related technical discipline. * Software Engineering : Strong proficiency in Python. * ML Frameworks : Extensive hands-on experience with PyTorch.

VTG

Data Scientist

Mclean, VA · On-site

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) * Strong ... field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

VTG

Data Scientist

Chantilly, VA

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) * Strong ... field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

VTG

Data Scientist

Herndon, VA

Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) * Strong ... field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

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How much do pytorch phd jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for pytorch phd in the United States is $29.44, according to ZipRecruiter salary data. Most workers in this role earn between $25.48 and $32.93 per hour, depending on experience, location, and employer.

What are some common challenges faced by researchers in a PyTorch-focused PhD role?

Researchers in a PyTorch-focused PhD role often encounter challenges such as debugging complex deep learning models, managing computational resources effectively, and staying updated with rapid advancements in machine learning frameworks. Collaboration with interdisciplinary teams is common, requiring clear communication of technical concepts. Additionally, balancing independent research with contributing to open-source projects or publishing can be demanding but is key to career growth in both academia and industry.

What are the key skills and qualifications needed to thrive as a PyTorch PhD researcher, and why are they important?

To thrive as a PyTorch PhD researcher, you need a strong background in machine learning, deep learning theory, and advanced mathematics, typically supported by a doctoral degree in computer science or a related field. Mastery of PyTorch, Python programming, and familiarity with tools like CUDA or cloud platforms are essential technical skills. Critical thinking, problem-solving, and effective communication help you excel in research collaborations and present findings clearly. These skills ensure you can design innovative models, contribute to scientific advancements, and communicate complex results to technical and non-technical audiences.

What is a PyTorch PhD?

A PyTorch PhD typically refers to a doctoral researcher who specializes in deep learning and artificial intelligence using the PyTorch framework. These researchers use PyTorch, an open-source machine learning library, to build, train, and test neural networks for tasks like computer vision, natural language processing, and reinforcement learning. PyTorch PhDs often contribute to academic research, publish papers, and develop new models and algorithms. They may also collaborate with industry partners to advance the state of AI technology.
Infographic showing various Pytorch Phd job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 66% Full Time, 31% Part Time, and 1% Contract. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution, with an average salary of $61,245 per year, or $29.4 per hour.

Wireless O-RAN AI/ML Engineer (PhD is required)

Innovatix Technology Partners

Bedminster, NJ

Other

Posted 22 days ago

Job description

We are seeking a talented and motivated Wireless Research Engineer with strong software and AI/ML capabilities to join our advanced networking team. Instead of traditional network deployment, this role sits at the cutting edge of Next-Gen cellular architecture: Open RAN (O-RAN).

In this role, you will apply your foundational knowledge of wireless communications to design, simulate, and develop intelligent solutions for Near-Real-Time (Near-RT) and Non-Real-Time (Non-RT) RAN Intelligent Controllers (RIC). You will leverage your coding skills in Python, alongside machine learning frameworks, to build the xApps and rApps that drive automation and optimize 5G network performance. This is the perfect launchpad for a telecom graduate eager to build software-driven, intelligent wireless infrastructure.

Key Responsibilities

  • Wireless Modeling & Simulation: Collaborate with senior engineers on system-level wireless simulations, network modeling, and cellular prototype testing.
  • App Development (xApps/rApps): Develop, test, and integrate intelligent xApps (Near-RT RIC) and rApps (Non-RT RIC) to control radio resources using Python.
  • RAN Optimization via AI/ML: Apply machine learning frameworks to solve telecom-specific challenges such as radio resource management (RRM), beamforming, traffic steering, and interference mitigation.
  • Telecom Data Analytics: Process and analyze large streams of live RAN telemetry and network KPI data using SQL database.
  • Standards Alignment: Study and implement O-RAN Alliance specifications to ensure prototype solutions align with evolving industry standards.

Required Skills & Qualifications

  • Education: PhD in Electrical Engineering, Telecommunications Engineering, or a closely related field with a heavy focus on wireless systems.
  • Wireless Deep Dive: A rock-solid foundational understanding of Wireless Communications, cellular network architecture (4G/5G), and radio frequency (RF) or protocol layer concepts.
  • O-RAN & RIC Exposure: Strong academic familiarity or project work involving O-RAN architecture, RIC platforms, and split-architecture concepts.
  • Programming & Software: High proficiency in Python, with the ability to write clean, structured code for network applications.
  • AI/ML Application: Hands-on experience (via academic research, capstone projects, or internships) applying ML libraries like TensorFlow or PyTorch to solve engineering or signal processing problems.
  • Data Basics: Familiarity with managing data via SQL and exposure to containerized environments (Docker/Kubernetes).

Apply