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Tensorflow Pytorch Jobs in Dallas, TX (NOW HIRING)

Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). * Proficiency in using analytics platforms like Databricks for large-scale data processing.

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). * Proficiency in using analytics platforms like Databricks for large-scale data processing.

Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging Face. * Strong analytical and problem-solving skills with a keen eye for detail. * Excellent ...

Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging Face. * Strong analytical and problem-solving skills with a keen eye for detail. * Excellent ...

Sr Software Engineer AI-ML

Irving, TX · On-site

$117K - $155K/yr

Sr Software Engineer AI-ML Require a blend of strong programming proficiency (especially Python - expert level), deep learning frameworks (PyTorch, TensorFlow), and data engineering skills to build ...

AI Engineer, Principal

Dallas, TX · Remote

$147K - $210K/yr

Strong programming skills in Python, TensorFlow, PyTorch, and other AI frameworks. * Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. What we ...

Sr Gen AI Engineer

Dallas, TX · On-site

$87K - $140K/yr

Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX * Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies with Docker and kubernetes

Sr Gen AI Engineer

Coppell, TX · On-site

$87K - $140K/yr

Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX * Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies with Docker and kubernetes

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

... TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs. • Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP). • Experience in building Asynchronous ...

Sr Software Engineer AI-ML

Irving, TX

$117K - $155K/yr

Sr Software Engineer AI-ML Require a blend of strong programming proficiency (especially Python - expert level), deep learning frameworks (PyTorch, TensorFlow), and data engineering skills to build ...

Gen AI Lead

Dallas, TX · On-site

$138K - $170K/yr

Git, TensorFlow, PyTorch, PySpark, AWS, MLflow, Docker, Kubernetes, Databricks, SparkSQL, OpenCV, Azure, YOLO, Scikit-Learn, FastAPI, Flask, Django, Keras, Pandas, NumPy, Polars, SciPy, Matplotlib ...

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

Advanced Python skills; experience with ML/NLP libraries (Hugging Face, TensorFlow, PyTorch). * Proven success building conversational agents with Vertex AI and Dialogflow CX/ES. * Proficiency in GCP ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). * Hands-on experience with PySpark for big data processing and model ...

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Tensorflow Pytorch information

See Dallas, TX salary details

$37.1K

$121.4K

$194.4K

How much do tensorflow pytorch jobs pay per year?

As of Jun 12, 2026, the average yearly pay for tensorflow pytorch in Dallas, TX is $121,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $134,500.00 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.

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.

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 cities near Dallas, TX are hiring for Tensorflow Pytorch jobs? Cities near Dallas, TX with the most Tensorflow Pytorch job openings: