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Python Tensorflow Numpy Jobs (NOW HIRING)

Snowrelic Inc

Python Developer

Charlotte, NC · On-site

$49 - $67.75/hr

Leverage Python libraries like NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, and TensorFlow for data analysis and machine learning tasks (advantageous but optional). * Collaborate with cross ...

Purple Drive Technologies

Python Developer

Tampa, FL · On-site

$47.50 - $65.50/hr

Hands-on expertise with TensorFlow, PyTorch, or Scikit-Learn . * Strong understanding of ... Experience with data libraries such as Pandas and NumPy . * Strong data preprocessing and feature ...

Nvidia

OR

$121K - $163K/yr

In the last decade, Python has become the de-facto programming language for practitioners in AI, data science and HPC, through popular frameworks such as NumPy, SciPy, TensorFlow and PyTorch. These ...

Tata Consultancy Services

Python Automation Developer

Plano, TX · On-site

$48.50 - $66.75/hr

Python Libraries such as NumPy; Pandas; Scikit-learn; TensorFlow and PyTorch; • Framework: Django ; Flask; FastAPI • Web Scraping and HTTP: Beautiful Soup; Scrapy • BACHELOR OF COMPUTER SCIENCE ...

Tata Consultancy Service Limited

AI Engineer

Cary, NC · On-site

$100K - $120K/yr

... NumPy) • Experience deploying models using APIs, Docker, and cloud platforms (AWS/Azure/GCP) • ... Python and ML/DL frameworks (TensorFlow, PyTorch, Scikit learn) • Integrate AI models into ...

Focus America Inc.

AI Engineer

Sunnyvale, CA

Machine Learning, AI,Python • Years of experience in each of the must-have skills: 7+ Years • ... Data processing using Pandas, NumPy, SQL, PySpark * Experience building and deploying models in ...

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How much do python tensorflow numpy jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for python tensorflow numpy in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What are some common challenges faced when working with Python, TensorFlow, and NumPy in a production environment?

Professionals using Python, TensorFlow, and NumPy in production often encounter challenges such as managing dependencies and package versions, optimizing model performance for real-time inference, and ensuring seamless integration with existing data pipelines. Debugging and tracking numerical errors or inconsistencies across different environments can also require extra attention. Collaborating effectively with data engineers, DevOps, and other team members is crucial to deploy robust machine learning solutions that scale reliably.

What are Python TensorFlow and NumPy?

Python is a versatile programming language widely used in data science and machine learning. TensorFlow is an open-source library developed by Google for numerical computation and building machine learning models, especially deep learning. NumPy is a popular Python library for numerical operations, providing support for large, multi-dimensional arrays and matrices. Together, these tools enable efficient development of machine learning algorithms and data processing workflows.

What is the difference between Python Tensorflow Numpy vs Data Scientist?

AspectPython Tensorflow Numpy
Primary FocusData manipulation, numerical computing, machine learning model development
Required SkillsPython programming, data analysis, machine learning frameworks
Work EnvironmentData science teams, AI research, software development
Common UsageBuilding and training machine learning models, data preprocessing

Python Tensorflow Numpy are tools and libraries used within data science roles to develop machine learning models and analyze data. Data Scientists utilize these tools to process data, build models, and derive insights, making their work heavily reliant on such technologies. While Python Tensorflow Numpy are technical libraries, Data Scientists are professionals who apply these tools in real-world projects, often combining them with statistical analysis and domain expertise.

What are the key skills and qualifications needed to thrive as a Python TensorFlow/Numpy Developer, and why are they important?

To thrive as a Python TensorFlow/Numpy Developer, you need strong programming skills in Python and a solid understanding of machine learning concepts, supported by relevant education or certifications in computer science, data science, or related fields. Familiarity with TensorFlow, Numpy, and version control systems like Git is typically required, along with experience using Jupyter notebooks and cloud platforms. Problem-solving abilities, attention to detail, and effective communication skills help developers translate data requirements into robust, scalable solutions. These skills are critical for building accurate machine learning models and collaborating efficiently within development teams or with stakeholders.
Infographic showing various Python Tensorflow Numpy job openings in the United States as of May 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 $121,932 per year, or $58.6 per hour.
Machine Learning Artificial Intelligence Engineer

Machine Learning Artificial Intelligence Engineer

Apex Informatics

Remote

$117K - $140K/yr

Contractor

Posted 10 days ago

Job description

  1. Strong project experience in Machine Learning, Big Data, NLP, Deep Learning, RDBMS is must.
  2. Strong project experience with Amazon Web Services and Cloudera Data Platform is must.
  3. 4-5 experience building data pipelines using Python, MLLib, PyTorch, TensorFlow, Numpy/Scipy/Pandas, Spark, Hive,
  4. 4-5 years of programming experience in AWS, Linux and Data Science notebooks is must.
  5. Strong experience with REST API development using Python frameworks (Django, Flask etc.).
  6. Micro Services/Web service development experience using Spring framework is highly desirable

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