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Python Tensorflow Numpy Jobs (NOW HIRING)

Mindrift

Machine Learning Developer (Freelance)

$90/hr

Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn ... Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain) * Strong written English (C1+). How ...

Amazon

Sr. Applied Scientist, Special Projects

Seattle, WA · On-site

$104K - $142K/yr

... Python or related language - Experience with neural deep learning methods and machine learning ... Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop ...

Tata Consultancy Services

AI Engineer

Cary, NC · On-site

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

eTeam

Senior AI/ML Engineer

Sunnyvale, CA · On-site

$122K - $167K/yr

The role involves strong programming experience in Python, a solid understanding of Machine ... TensorFlow) • Hands-on experience with Generative AI / LLMs (OpenAI, Azure OpenAI, open-source ...

Select Minds LLC

Data Scientist

Dallas, TX

$65 - $75/hr

Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain ...

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How much do python tensorflow numpy jobs pay per hour?

As of Jun 8, 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.

Sr. Java Developer with strong AI/ML exp

Saransh Inc

Lake Mary, FL • On-site

$50 - $63.75/hr

Contractor

Posted 15 days ago

Job description

Role: Sr. Java Developer with strong AI/ML exp
Location: Lake Mary, FL (Onsite from Day 1)
Job Type: Long Term Contract
 
Job Description:
 
Relevant Experience: 10+ Years

Technologies:

  • Transaction Monitoring AML, Fraud, Sanctions Screening OFAC, CDD KYC, Trade Surveillance, Financial Crimes Risk Assessment.
  • Python NumPy, Pandas, TensorFlow/PyTorch.
  • Java Spring Boot, multithreading, JVM optimization.

Required Skills:

  • 10 or more years of experience in data science.
  • Ability to work effectively in a dynamic group that has several concurrent projects.
  • Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.
  • Machine learning Artificial Intelligence Implement algorithms and statistical models to automate data analysis, data profiling and data validation.
  • Develop programs and analyze large datasets to uncover answers to complex problems. Should be comfortable writing code and working in a variety of programming languages, such as Java, Python, and SQL
  • Hands on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine tuning, or agent-based architectures.
  • Experience with AI frameworks like Langchain, Llama Index, OpenAI, or similar tools.
  • Proficient with Java, Python, SQL.
  • Build APIs and microservices to support AI functionalities.
  • Optimize code for performance, scalability, and reliability.
  • Participate in code reviews, testing, and debugging.
  • Exposure to MLOps practices and tools.
  • Proficiency in Python NumPy, Pandas, TensorFlow/PyTorch, etc.
  • Strong knowledge of Java Spring Boot, multithreading, JVM optimization
  • Experience with RESTful APIs, cloud platforms (either AWS, GCP, or Azure), and containerization Docker, Kubernetes
  • Familiarity with version control systems Git and CI CD pipelines.
  • Experience with AI/ML frameworks and libraries.
  • Knowledge of data engineering tools e.g., Apache Kafka, Spark
  • NumPy, Pandas, TensorFlow/PyTorch, etc
  • Spring Boot, multithreading, JVM optimization.
  • Experience with AI ML frameworks and libraries.
  • Data engineering tools (e.g., Apache Kafka, Spark).
  • Experience preferably in one or many of these Transaction Monitoring AML, Fraud, Sanctions Screening OFAC, CDD KYC, Trade Surveillance, Financial Crimes Risk Assessment.