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Before And After School Python Machine Learning Jobs

As a Before & After School Teacher at Kids First, you will be responsible for planning and implementing fun, educational activities that inspire learning and growth. From arts and crafts to sports ...

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Before And After School Python Machine Learning information

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$13

$58

$86

How much do before and after school python machine learning jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for before and after school python machine learning 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 is the difference between Before And After School Python Machine Learning vs Data Analyst?

AspectBefore And After School Python Machine LearningData Analyst
Required CredentialsPython programming, basic machine learning knowledge, possibly certificationsStatistical skills, Excel, SQL, certifications like CAP or Microsoft certifications
Work EnvironmentEducational settings, coding labs, online platformsCorporate offices, data centers, consulting firms
Industry UsageEducational programs, tech workshops, online coursesBusiness intelligence, market research, reporting

While both roles involve data handling and technical skills, Before And After School Python Machine Learning focuses on teaching and applying machine learning in educational contexts, whereas Data Analysts interpret data to support business decisions. The skills overlap in Python and data analysis, but their applications and environments differ significantly.

More about Before And After School Python Machine Learning jobs
What cities are hiring for Before And After School Python Machine Learning jobs? Cities with the most Before And After School Python Machine Learning job openings:
What states have the most Before And After School Python Machine Learning jobs? States with the most job openings for Before And After School Python Machine Learning jobs include:
What job categories do people searching Before And After School Python Machine Learning jobs look for? The top searched job categories for Before And After School Python Machine Learning jobs are:
Infographic showing various Before And After School Python Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Python Unix machine learning Support Engineer

Python Unix machine learning Support Engineer

Centraprise

Chandler, AZ • On-site

Full-time

Re-posted 14 days ago


Job description

Job Title : Python Unix machine learning Support Engineer
Job Location : Chandler, AZ (ONSITE)
Job Type : Full-Time
Job Description:
Python Unix machine learning Support Engineer
Must Have Technical/Functional Skills
Unix, ShellScripting, Python, Machine learning, Production Support
Roles & Responsibilities
• System Configuration: Configuring Unix systems to meet specific requirements and standards.
• Troubleshooting: Identifying and resolving issues with Unix systems and applications.
• Scripting: Automating repetitive tasks using Python scripts.
• Performance Optimization: Analyzing and improving the performance of Unix systems.
• Documentation: Creating and maintaining system documentation and guides.
• Collaboration: Working with other teams and departments to ensure Unix systems are integrated and functional.
• Implement AI workflows using Python, agent frameworks, and orchestration tools
• Develop LLM pipelines including prompt engineering, prompt chaining, memory, tool calling, and multi-agent coordination
• Integrate LLMs with enterprise systems and APIs
• These roles are essential for maintaining the reliability and efficiency of Unix-based systems, and Python skills
can be leveraged to automate and streamline these tasks.
• Designed, developed, and deployed machine learning models using supervised and unsupervised learning
techniques to solve real world business problems.
• Worked with Python ML libraries including Scikit learn, TensorFlow, PyTorch, Pandas, NumPy, and Matplotlib.
• Deployed models using REST APIs, Docker, or cloud platforms (AWS / Azure / GCP) to support production
use cases.