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Junior Ai Machine Learning Python Jobs in Charlotte, NC

Eversoft Technologies LLC

AI Architect

Charlotte, NC · On-site

Apply AI capabilities -- design and integrate AI / GenAI / machine-learning components into ... Languages & Prototyping -- proficiency in Python and/or Java (or comparable); rapid prototyping ...

Bespoke Labs

Machine Learning Engineer

Charlotte, NC · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops ...

Bespoke Labs

Machine Learning Engineer

Rock Hill, SC · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops ...

Nastech Global

GEN AI Architect

Charlotte, NC · On-site

... at Python, LLM prompting, Azure OpenAI service, and other Gen AI related Azure services such as ... Solid understanding of machine learning, NLP, computer vision, and other relevant AI fields. Proven ...

Varsity Tutors

Python Tutor

Matthews, NC · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Emphasizes readable, maintainable code and connects Python to machine learning, web scraping ...

Varsity Tutors

Python Tutor

Charlotte, NC · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Emphasizes readable, maintainable code and connects Python to machine learning, web scraping ...

Randstad Digital

AI Engineer

Charlotte, NC · On-site

$51.59 - $61.59/hr

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Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Strong proficiency in Python programming, with experience building scalable AI/ML systems. Hands-on ...

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Junior Ai Machine Learning Python information

See Charlotte, NC salary details

$45.4K

$92.3K

$138.7K

How much do junior ai machine learning python jobs pay per year?

As of Aug 14, 2026, the average yearly pay for junior ai machine learning python in Charlotte, NC is $92,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,300.00 and $93,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a junior AI machine learning Python engineer, and why are they important?

To thrive as a Junior AI Machine Learning Python Engineer, you need a solid understanding of Python programming, statistics, and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, Scikit-learn, Jupyter Notebooks, and version control systems such as Git is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork skills help individuals excel in collaborative and fast-evolving technical environments. These competencies are crucial for developing robust AI solutions, learning from senior colleagues, and adapting to the rapidly changing landscape of machine learning.

What does a junior AI machine learning Python engineer do?

A Junior AI Machine Learning Python engineer assists in developing, testing, and maintaining machine learning models using Python. They typically work with data preparation, preprocessing, and applying basic algorithms to solve real-world problems. Under the guidance of senior engineers, they help implement solutions, evaluate model performance, and may contribute to the deployment of models into production environments. Their role often includes learning best practices in coding, software development, and collaborating with data scientists and engineers.

What are some typical projects or tasks a junior AI machine learning Python developer might work on in their first year?

As a Junior AI/Machine Learning Python developer, you can expect to work on tasks such as cleaning and preparing datasets, developing and testing simple machine learning models, and assisting in the implementation of algorithms under the supervision of senior team members. You may also help automate data pipelines, write scripts for data extraction, and contribute to model evaluation and reporting. Collaboration with data scientists, software engineers, and product managers is common, providing valuable learning opportunities and exposure to the full machine learning workflow.

What is the difference between Junior Ai Machine Learning Python vs Data Analyst?

AspectJunior Ai Machine Learning PythonData Analyst
Required SkillsPython, Machine Learning, AI concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
CertificationsPython certifications, AI/ML coursesData analysis or visualization certifications
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Industry UsageDeveloping AI models, machine learning pipelinesInterpreting data, generating reports, supporting decision-making

Junior Ai Machine Learning Python roles focus on developing AI models using Python and machine learning techniques, often in tech-driven environments. Data Analysts primarily interpret data, create visualizations, and support business decisions. While both roles require analytical skills, AI/ML roles demand programming and AI-specific knowledge, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Junior Ai Machine Learning Python jobs in Charlotte, NC?

For Junior Ai Machine Learning Python jobs in Charlotte, NC, the most frequently searched job titles are:

What job categories do people searching Junior Ai Machine Learning Python jobs in Charlotte, NC look for?

The top searched job categories for Junior Ai Machine Learning Python jobs in Charlotte, NC are:

What cities near Charlotte, NC are hiring for Junior Ai Machine Learning Python jobs?

Cities near Charlotte, NC with the most Junior Ai Machine Learning Python job openings:

Junior Ai Machine Learning Python jobs near you
Infographic showing various Junior Ai Machine Learning Python job openings in Charlotte, NC as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $92,341 per year, or $44.4 per hour.

AI Architect

Eversoft Technologies LLC

Charlotte, NC • On-site

Other

Posted 4 days ago

Job description

AI Architect – 2 positions
Charlotte, NC 3 days/week onsite (Need local candidates)
Job Description for AI Architect:
We are seeking two experienced Lead Architects on a contract basis to strengthen delivery of architecture work across our technology portfolio. These roles operate at the Lead Architect level and partner closely with our internal architecture team, engineering leads, and business stakeholders.
The right candidates are hands-on, AI-fluent architects who can quickly translate business and technical needs into clear architecture artifacts and stand up working prototypes to prove out ideas fast. They should be comfortable moving between big-picture design and rapid, tangible experimentation.
Key Responsibilities
Assemble architecture designs — produce clear, end-to-end architecture artifacts: solution designs, reference architectures, diagrams, patterns, and architecture decision records.
Apply AI capabilities — design and integrate AI / GenAI / machine-learning components into solutions, and advise on appropriate patterns, tooling, and trade-offs.
Drive rapid prototypes — build quick proofs of concept and working prototypes to validate architecture decisions, de-risk options, and accelerate stakeholder alignment.
Partner across teams — work with engineering, product, and business partners to align architecture with delivery goals and non-functional requirements (security, scalability, resilience, cost).
Document and communicate — present designs and trade-offs clearly to both technical and non-technical audiences, and keep architecture documentation current and usable.
Uphold standards — apply enterprise architecture standards, controls, and best practices throughout design and prototyping.
Required Qualifications (Must-Have)
Demonstrable hands-on AI experience — practical work building, integrating, or architecting AI / GenAI / ML solutions.
Proven ability to put architecture details together — a track record of producing clear, complete architecture designs and documentation.
Ability to drive quick prototypes — rapidly stand up POCs and working prototypes to test and demonstrate ideas.
Senior, hands-on technical background operating at a Lead Architect level, with strong design fundamentals across modern application, integration, and cloud patterns.
Strong communication skills — able to explain architecture and trade-offs to technical teams and business stakeholders alike.
Self-directed and comfortable working across ambiguity to deliver tangible outcomes quickly.
Technical Skills
Representative technical skills for these roles. Candidates should bring strong depth across several of these areas — tailor to our stack as needed:
AI & Machine Learning — GenAI and large language models (LLMs), retrieval-augmented generation (RAG), agentic and prompt-engineering patterns, model APIs and integration, embeddings and vector stores; familiarity with common ML frameworks.
Cloud & Platform — hands-on experience with at least one major cloud (AWS, Azure, or Google Cloud Platform); containers and orchestration (Docker, Kubernetes); serverless services.
Architecture & Integration — microservices, event-driven and API-led design, REST / GraphQL APIs, messaging and streaming (e.g., Kafka), and enterprise integration patterns.
Data & Information Architecture — data modeling, relational and NoSQL databases (strong SQL), data lakes / warehouses, ETL / ELT pipelines, and data governance / metadata.
Languages & Prototyping — proficiency in Python and/or Java (or comparable); rapid prototyping, scripting, and notebook-based experimentation.
Engineering Practices — CI/CD, infrastructure as code (e.g., Terraform), Git-based version control, and automated testing.
Architecture Tooling — modeling and diagramming (C4, UML, or ArchiMate) and architecture decision records (ADRs).
Preferred Qualifications (Nice-to-Have)
The following are strong pluses and will differentiate candidates, but are not strict requirements:
Depth in data / information architecture — experience designing data models, information flows, data platforms, or enterprise information architecture.
Finance domain experience — prior work in Finance functions, especially Controllers / financial control and related processes.

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