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Junior Ai Machine Learning Python Jobs in South Carolina

Varsity Tutors

Python Tutor

Greenville, SC · 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

Florence, SC · 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

Columbia, SC · 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

Mount Pleasant, SC · 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 ...

TSMG

AI/ML Data Contributor

Columbia, SC · On-site

In this role, you will participate in tasks that help improve machine learning models, including ... Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ...

TSMG

AI/ML Data Contributor

Columbia, SC

In this role, you will participate in tasks that help improve machine learning models, including ... Perform AI/ML-related tasks such as data labeling, annotation, and content evaluation * Participate ...

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Junior Ai Machine Learning Python information

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 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 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 South Carolina?

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

What job categories do people searching Junior Ai Machine Learning Python jobs in South Carolina look for?

The top searched job categories for Junior Ai Machine Learning Python jobs in South Carolina are:

What cities in South Carolina are hiring for Junior Ai Machine Learning Python jobs?

Cities in South Carolina with the most Junior Ai Machine Learning Python job openings:

Junior Ai Machine Learning Python jobs near you

AI Evaluation Subject Matter Expert

Foxhole Technology

Charleston, SC • On-site

Full-time

Re-posted 10 days ago

Job description

Work Arrangement: Hybrid
Clearance: Active Secret w/TS Capability
Foxhole Technology provides robust cybersecurity and IT support capabilities for federal civilian and defense agencies. A recognized leader in navigating technology and security challenges, Foxhole delivers mission-focused innovations to answer evolving and complex needs. Our talented employee-owners provide agile, scalable services and solutions that solve operational gaps, operate critical systems, and protect and secure the enterprise - across the organization and around the world
Foxhole Technology is seeking an AI Evaluation SME to join an existing program. The AI Evaluation SME will support the assessment, testing, validation, and operational evaluation of artificial intelligence, machine learning, automation, analytics, and decision-support capabilities being considered for or integrated into the Navy's Next Generation CANES environment. This role will help ensure AI-enabled capabilities are mission-relevant, reliable, secure, explainable, measurable, and suitable for deployment within afloat, tactical, disconnected, intermittent, limited-bandwidth, and multi-security-domain environments.
The SME will develop evaluation frameworks, test methods, metrics, datasets, scenarios, risk assessments, and reporting products that help Navy and CACI stakeholders determine whether AI-enabled capabilities improve network operations, cyber defense, system administration, predictive maintenance, anomaly detection, configuration management, mission planning, or other CANES-related functions.
KEY RESPONSIBILITIES:
  • Serve as a senior technical advisor for AI evaluation, test planning, performance assessment, and operational suitability analysis in support of Next Generation CANES modernization.
  • Develop AI evaluation strategies, test plans, measures of effectiveness, measures of performance, success criteria, risk indicators, and evaluation scorecards.
  • Assess AI, machine learning, generative AI, automation, analytics, and decision-support capabilities for operational relevance, technical maturity, cyber risk, reliability, maintainability, explainability, human oversight, and fleet suitability.
  • Evaluate AI-enabled tools for use cases such as network monitoring, cyber anomaly detection, event correlation, predictive maintenance, help desk automation, configuration compliance, system health monitoring, log analysis, vulnerability prioritization, and operational decision support.
  • Design test scenarios that reflect Navy afloat operating conditions, including limited bandwidth, disconnected operations, contested cyber environments, cross-domain constraints, variable data quality, and platform-specific operational limitations.
  • Define data requirements, ground truth methods, evaluation datasets, labeling approaches, validation methods, and performance baselines for AI-enabled capabilities.
  • Assess AI model performance using appropriate metrics such as accuracy, precision, recall, false positive rate, false negative rate, latency, robustness, drift, confidence calibration, explainability, and operational impact.
  • Evaluate risks associated with hallucination, model brittleness, adversarial manipulation, data poisoning, prompt injection, bias, over-reliance, model drift, cybersecurity exposure, and failure modes in operational environments.
  • Support AI red teaming, cyber survivability assessment, adversarial testing, safety reviews, and responsible AI evaluation activities.
  • Develop human-machine teaming concepts, operator-in-the-loop workflows, trust calibration approaches, escalation procedures, and recommended guardrails for AI-enabled tools.
  • Produce technical reports, evaluation findings, executive summaries, test observations, data analysis products, and recommendations for Navy and CACI leadership.
  • Collaborate with systems engineers, cybersecurity engineers, software developers, data scientists, network engineers, operational testers, fleet users, and government stakeholders.
  • Support technical interchange meetings, design reviews, test readiness reviews, operational assessments, demonstrations, and acquisition decision support.
  • Provide SME input on AI governance, responsible AI implementation, model lifecycle management, configuration control, sustainment, monitoring, and continuous evaluation.

REQUIRED QUALIFICATIONS:
  • Bachelor's degree in computer science, data science, artificial intelligence, engineering, mathematics, statistics, cybersecurity, operations research, information systems, or a related technical discipline preferred. Advanced degree preferred.
  • Additional years of directly relevant AI evaluation, test, cybersecurity, Navy, or DoD mission system experience may be considered in lieu of a degree.
  • Demonstrated experience evaluating AI, machine learning, data analytics, automation, or decision-support systems in defense, intelligence, cybersecurity, network operations, enterprise IT, or mission system environments.
  • Strong understanding of AI / ML evaluation methods, test design, performance metrics, validation approaches, model limitations, and operational risk assessment.
  • Experience developing test plans, evaluation frameworks, measures of effectiveness, measures of performance, data collection plans, and technical reports.
  • Familiarity with cybersecurity, enterprise networks, tactical networks, system monitoring, anomaly detection, log analytics, or network operations use cases.
  • Ability to assess AI-enabled systems in operationally constrained environments, including limited bandwidth, degraded connectivity, edge computing, and mission-critical infrastructure.
  • Understanding of responsible AI concepts, including transparency, explainability, human oversight, robustness, security, bias, accountability, and lifecycle monitoring.
  • Experience working with cross-functional engineering, cyber, data science, software, test, and government stakeholder teams.
  • Strong written and verbal communication skills, including the ability to brief complex AI evaluation findings to technical and non-technical audiences.
  • Active DoD Secret clearance.

DESIRED QUALIFICATIONS:
  • Experience supporting Navy, DoD, tactical edge, afloat, C4I, cyber, enterprise IT, or mission command systems.
  • Familiarity with CANES, Navy afloat networks, ADNS, NAVWAR programs, RMF, cyber survivability testing, operational test, developmental test, or fleet experimentation.
  • Experience evaluating generative AI, large language models, retrieval-augmented generation, autonomous agents, AI-assisted cyber tools, AI-enabled network operations, or predictive analytics systems.
  • Knowledge of DoD responsible AI guidance, NIST AI Risk Management Framework concepts, RMF, Zero Trust, DevSecOps, MLOps, model monitoring, or secure software supply chain practices.
  • Experience with data analysis tools, scripting, statistical evaluation, dashboards, test automation, or model performance analysis.
  • Experience with AI red teaming, adversarial ML, cyber test events, operational assessments, or acquisition decision support.
  • Top Secret clearance or SCI eligibility.

Requirements of position: Think analytically, effective verbal and written communication skills, make decisions, observe/remember details, interpret data, concentrate on tasks, adjust to change, handle stress/emotions. Regular attendance, maintain work schedule, attend meetings, meet deadlines, keyboard/type, handle confidential information, use math/calculations, stay organized, operate office equipment, may direct others. May be exposed to dust/dirt, humidity, and noise
Foxhole Technology is an Equal Opportunity Employer and makes hiring decisions without regard to race, color, religion, sex (including pregnancy, childbirth and sexual orientation), national origin, age, disability, genetic information, military/veteran status, or any other protected class.

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