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Tensorflow Pytorch Jobs (NOW HIRING)

Python (Advanced), Machine Learning frameworks (TensorFlow/PyTorch) Mandatory: Kubernetes experience and cloud-native development practices Required Skills & Experience • Primary Technologies:

Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). * Proficiency in data manipulation and analysis using SQL and data processing tools (e.g., Apache ...

Apply machine learning algorithms using libraries such as Scikit-learn, TensorFlow, or PyTorch . * Evaluate model performance and tune hyperparameters for improved accuracy. Visualization & Reporting

AI enabled chatbot Langchain TensorFlow Java PyTorch RASA Python AI Experience: 10-14 yrs Required Skills: • Proven experience in developing AI agents, chatbots, or conversational AI systems. • ...

AI Architect

Houston, TX · On-site

$90/hr

... TensorFlow, PyTorch, scikit-learn). • Proficiency in data manipulation and analysis using SQL and data processing tools (e.g., Apache Spark, Hadoop). • Experience with cloud platforms (e.g., AWS ...

AI Engineer

Cary, NC · On-site

$100K - $120K/yr

... TensorFlow, PyTorch, Scikit learn) • Experience working with structured and unstructured data • Knowledge of SQL and data processing libraries (Pandas, NumPy) • Experience deploying models ...

ExpertiseGood knowledge of AIML frameworks (TensorFlow, PyTorch,etc.) and libraries Experience with cloud based AIML platforms (e.g. Dataiku, AWS.) Strong programming skills in Python, Java or C ...

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Tensorflow Pytorch information

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$37.5K

$122.7K

$196.5K

How much do tensorflow pytorch jobs pay per year?

As of May 30, 2026, the average yearly pay for tensorflow pytorch in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Deep Learning Engineer specializing in TensorFlow and PyTorch, and why are they important?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

More about Tensorflow Pytorch jobs
What cities are hiring for Tensorflow Pytorch jobs? Cities with the most Tensorflow Pytorch job openings:
What states have the most Tensorflow Pytorch jobs? States with the most job openings for Tensorflow Pytorch jobs include:
Infographic showing various Tensorflow Pytorch job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 90% Full Time, 4% Part Time, and 5% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Senior Python AI/ML Engineer (TensorFlow/PyTorch) - Q125

Senior Python AI/ML Engineer (TensorFlow/PyTorch) - Q125

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Medical, Retirement, PTO

Posted 24 days ago


Job description

Overview:
R2 Technologies Corporation (R2), headquartered in Alpharetta, GA, is a leading IT services provider specializing in Java, .NET, Big Data, Cloud Computing (AWS, GCP, Azure), Artificial Intelligence (AI), Machine Learning (ML), software development, project management, SAP, and enterprise resource planning (ERP). We empower clients-from startups to Fortune 1000 companies-with scalable, platform-based solutions and data-driven insights using modern cloud technologies. Our commitment to blending highly skilled talent with innovative productivity platforms ensures rapid delivery of business value, making us one of the most respected and trusted technology companies in the United States. At R2, we're passionate about driving operational excellence and competitive advantage for our clients through cutting-edge AI, ML, and cloud solutions. Join our team and help shape the future of technology innovation!
Senior Python AI/ML Engineer (TensorFlow/PyTorch)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking an accomplished Senior Python AI/ML Engineer to develop advanced AI solutions using Python with TensorFlow or PyTorch. This role focuses on building and training machine learning models within scalable data pipelines.
Key Responsibilities
  • Design and implement AI/ML models using Python with TensorFlow or PyTorch for predictive insights.
  • Build and optimize data pipelines to preprocess and feed data into model training workflows.
  • Train, evaluate, and deploy machine learning models in production environments.
  • Collaborate with data scientists to refine models and improve accuracy and performance.
  • Ensure scalability and efficiency of AI solutions through robust pipeline design.
  • Monitor and troubleshoot model performance to maintain production reliability.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience in Python development with a focus on AI and machine learning.
  • Proficiency in building and training models with TensorFlow or PyTorch for real-world applications.
  • Experience with data pipelines for preprocessing and managing ML training datasets.
  • Strong understanding of AI/ML workflows and their integration into production systems.

Preferred Qualifications
  • Familiarity with cloud platforms like AWS or Azure for deploying AI/ML models.
  • Exposure to advanced ML techniques like deep learning or reinforcement learning.
  • Knowledge of GPU optimization for accelerating model training processes.

Compensation & Benefits
  • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
  • Opportunities for professional growth and upskilling in AI and cloud technologies.

R2 Technologies Corporation is an equal opportunity employer and values diversity in the workplace.
Skills:
Python, AI, Machine Learning, TensorFlow, PyTorch, Data Pipeline, Model Training