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Tensorflow Pytorch Jobs in Dallas, TX (NOW HIRING)

Machine Learning Engineer - NJ

Addison, TX · On-site

$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.

Senior AI Engineer

Dallas, TX · On-site

$103K - $142K/yr

Proficiency in programming languages such as Python and familiarity with libraries such as TensorFlow, PyTorch, and Scikit-learn. * Experience with cloud-based AI services such as AWS, Google Cloud ...

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 ...

Expert AI Engineer

Dallas, TX · On-site

$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 ...

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 ...

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

... as TensorFlow, PyTorch, or scikit-learn. • Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement ...

Predictive Analytics Engineer

Dallas, TX · On-site

$100K - $120K/yr

TensorFlow * PyTorch * Experience with statistical modeling, predictive analytics, and feature engineering. * Strong understanding of: * Regression Analysis * Hypothesis Testing * Probability ...

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 ...

Strong proficiency in Python programming and related libraries (e.g., TensorFlow, PyTorch, scikit-learn). * Experience with Large Language Models (LLMs), Prompt Engineering, and RAG implementation.

... TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain or equivalent • Experience in AWS core services, SageMaker • Bachelor's degree or foreign equivalent required from an accredited ...

Sr Software Engineer AI-ML

Irving, TX · On-site

$113K - $149K/yr

Required : • Strong programming proficiency (especially Python - expert level) • Deep learning frameworks (PyTorch, TensorFlow) • Data engineering skills to build and deploy models • ...

... TensorFlow, PyTorch, or Scikit-learn. · Solid understanding of supervised, unsupervised, and reinforcement learning techniques. · Experience with data preprocessing, feature engineering, model ...

Fluent in Python and C/C++, and at home in TensorFlow, PyTorch, or similar platforms. * Problem solver and communicator - ready to connect, share, and lead in a diverse, cross-functional team. Bonus ...

Showing results 41-60

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 Aug 9, 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?

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 are popular job titles related to Tensorflow Pytorch jobs in Dallas, TX? For Tensorflow Pytorch jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Dallas, TX look for? The top searched job categories for Tensorflow Pytorch jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Tensorflow Pytorch jobs? Cities near Dallas, TX with the most Tensorflow Pytorch job openings:
Infographic showing various Tensorflow Pytorch job openings in Dallas, TX as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $121,417 per year, or $58.4 per hour.

Machine Learning Engineer - NJ

Photon

Addison, TX • On-site

$54 - $71.50/hr

Full-time

Re-posted yesterday


Job description


Summary:
We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and engineering teams to solve complex business problems, identify data-driven opportunities, and create personalized experiences for customers. You will be responsible for building end-to-end machine learning solutions, implementing models in production, and working with various data frameworks and tools such as Python, Spark, and Databricks.
Key Responsibilities: Analytics Model Development:
  • Analyze use cases and design appropriate analytics models using statistical and machine learning algorithms tailored to specific business requirements.
  • Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights.
  • Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.

Data Engineering and Preparation:
  • Extend and augment company data with third-party data to enrich analytics capabilities.
  • Enhance data collection procedures to include necessary information for building analytics systems.
  • Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing data formats using Python data frameworks (e.g., Pandas, NumPy).

Machine Learning Model Implementation:
  • Implement machine learning models, considering both performance and scalability using tools like PySpark in Databricks.
  • Design and build infrastructure to facilitate large-scale data analytics and experimentation.
  • Work with tools like Jupyter Notebooks for data exploration and model development.

What We're Looking For:
  • Educational Background: Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A PhD is preferred but not necessary.
  • Experience:
    • At least 5 years of experience in data analytics, with a strong understanding of core statistical algorithms such as classification and regression analysis.
    • High-level knowledge of analytics use cases such as language analysis, assortment optimization, promotional planning, dynamic pricing, markdown optimization, labor scheduling, and optimization.
  • Technical Skills:
    • 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.
    • At least 4 years of continuous experience with Spark, particularly PySpark implementation.
    • Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.