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Internship Ai Strategy Jobs (NOW HIRING)

Support IntelliTrans' data streaming strategy by designing data pipelines and feature engineering ... internships and professional experience considered). * Demonstrated experience building and ...

Intern (Technical-Engineering), 17871

Sunnyvale, CA ยท On-site

$19.75 - $25.50/hr

General Information Job Title Summer 2026 Internship - AI/ML Training Pipeline Engineer Internship ... data generation strategies โ€ข Build automation infrastructure including scripts for data ...

Our primary areas of strategic focus include talent acquisition, individual and organizational ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

Our primary areas of strategic focus include talent acquisition, individual and organizational ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

Our primary areas of strategic focus include talent acquisition, individual and organizational ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

Our primary areas of strategic focus include talent acquisition, individual and organizational ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

The models that drive our trading strategies have evolved considerably over the last 10 years, from ... The XTY AI Research Internship ** Please note that we are now only accepting applications from ...

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How much do internship ai strategy jobs pay per hour?

As of Jul 1, 2026, the average hourly pay for internship ai strategy in the United States is $23.07, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $28.85 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Strategy Intern, and why are they important?

To thrive as an AI Strategy Intern, you generally need a background in computer science, data analysis, and business strategy, often supported by progress toward a relevant degree. Familiarity with data analytics tools (such as Python, SQL), machine learning frameworks, and project management software is typically expected. Excellent analytical thinking, problem-solving, and communication skills help you synthesize technical insights and convey strategic recommendations to diverse stakeholders. These abilities are crucial for bridging technical AI concepts with business objectives and driving impactful innovation within organizations.

What is the difference between Internship Ai Strategy vs Data Analyst Intern?

AspectInternship Ai StrategyData Analyst Intern
Required SkillsBasic understanding of AI, data analysis, programming (Python, SQL)Data collection, cleaning, analysis, visualization skills
Work EnvironmentCollaborative teams focusing on AI projects, product developmentData-focused tasks within business units, reporting
Industry UsageTech companies, AI startups, R&D departmentsFinance, marketing, healthcare, retail sectors

Internship Ai Strategy roles typically involve supporting AI project development, understanding AI concepts, and working with cross-functional teams. Data Analyst Interns focus on analyzing data sets, generating reports, and providing insights. While both roles require analytical skills, Internship Ai Strategy emphasizes AI knowledge and strategic thinking, whereas Data Analyst Intern roles center on data manipulation and visualization.

What is an Internship in AI Strategy?

An Internship in AI Strategy is an entry-level position where students or recent graduates work with organizations to help develop and implement strategies involving artificial intelligence. Interns typically assist with research, data analysis, market assessments, and the formulation of AI-driven business solutions. This role is ideal for those interested in how AI technologies can be leveraged to achieve business objectives. Interns gain valuable experience by working alongside AI experts and strategic planners, contributing to projects that shape the future direction of organizations.

What types of projects or responsibilities can I expect during an AI Strategy internship?

As an AI Strategy intern, you can expect to work closely with cross-functional teams to analyze business problems and identify areas where AI technologies can add value. Typical responsibilities may include conducting market research, supporting the development of AI roadmaps, preparing presentations for stakeholders, and assisting in the evaluation of data-driven solutions. You'll also likely participate in brainstorming sessions, collaborate with data scientists and engineers, and help assess the feasibility and impact of proposed AI initiatives. This hands-on exposure provides a strong foundation for understanding both the technical and business sides of AI strategy.
More about Internship Ai Strategy jobs
What cities are hiring for Internship Ai Strategy jobs? Cities with the most Internship Ai Strategy job openings:
What are the most commonly searched types of Ai Strategy jobs? The most popular types of Ai Strategy jobs are:
What states have the most Internship Ai Strategy jobs? States with the most job openings for Internship Ai Strategy jobs include:
Infographic showing various Internship Ai Strategy job openings in the United States as of June 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $47,988 per year, or $23.1 per hour.
Applied AI Engineer

Applied AI Engineer

IntelliTrans

Atlanta, GA โ€ข On-site

Full-time

Posted 27 days ago


Job description

IntelliTrans, (ITL), a subsidiary of Roper Technologies, Inc. (NYSE: ROP) is seeking an Applied AI Engineer to join our team, hybrid in Atlanta, GA.

Position Summary: The Applied AI Engineer a key member of the AI and Data Science Team, responsible for designing, developing, and deploying production AI/ML systems that power IntelliTransโ€™ intelligent freight management platform. This role blends applied AI engineering with data science fundamentals, including building and evaluating agentic AI systems, developing LLM-powered features, designing ML pipelines, and creating intelligent automation workflows. The ideal candidate is comfortable operating across the full spectrum from exploratory data analysis to production AI system deployment and is energized by applying AI to real-world logistics challenges.

Essential Duties and Responsibilities:

AI/ML Engineering and Agentic AI
  • Design, build, and evaluate agentic AI systems using Agentic AI platforms and related frameworks for freight management use cases (e.g., shipment exception handling, real time visibility, ETA intelligence).
  • Develop and optimize LLM-powered features, including prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and tool-calling agents integrated into workflows
  • Build and maintain ML model evaluation frameworks with structured metrics, AI-assisted judges, and human feedback loops modern frameworks and DB Catalog tools
  • Contribute to developing browser automation + AI hybrid systems, including data extraction pipelines using Playwright and Claude.
ย ย Data Science and Analytics
  • Analyze complex, large-scale freight and logistics datasets to generate actionable business insights for internal stakeholders and customers.
  • Develop and maintain predictive models for supply chain KPIs, including ETA prediction, freight audit anomaly detection, and shipment pattern analysis.
  • Support IntelliTransโ€™ data streaming strategy by designing data pipelines and feature engineering workflows that bridge the System of Record and System of Intelligence layers.
  • Build and iterate on dashboards and analytical tools using SQL, Analytics, and supporting visualization platforms.
Platform and Infrastructure
  • Develop production-grade Python services (FastAPI, async patterns) that integrate ML models and AI agents into the IntelliTrans platform.
  • Collaborate with the architecture team on AWS cloud infrastructure (ECS Fargate, SQS, S3, CloudWatch, Terraform) for model deployment and agent runtime scaling.
  • Contribute to CI/CD pipelines, observability instrumentation (OpenTelemetry, structlog), and MLOps best practices for model lifecycle management.
Collaboration and Strategy
  • Partner with Product Management to translate the AI agent roadmap into technical specifications and delivery plans aligned with IntelliTransโ€™ 3โ€“5 year data and AI strategy.
  • Use modern Code Assistance tools such as Claude Code to write software.
  • Effectively handle multiple projects simultaneously in a deadline-driven environment.

ย 

QUALIFICATIONS AND BACKGROUND

ย Education:ย ย ย ย ย ย  Bachelorโ€™s degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related discipline required. Masterโ€™s degree in a quantitative field (Data Science, AI/ML, Engineering, Mathematics, or Statistics) preferred.

Experience: ย ย ย ย ย ย  Minimum 2โ€“4 years of professional experience in AI engineering, ML engineering, or applied data science (combination of internships and professional experience considered).

  • Demonstrated experience building and deploying AI systems, ML models, or LLM-powered applications in a production environment.
  • Experience with modern data platforms, preferably Databricks (Delta Lake, MLflow, Unity Catalog) or equivalent (Snowflake, AWS SageMaker).
  • Experience in supply chain, logistics, freight management, or transportation technology is strongly preferred.
  • Hands-on experience with agentic AI concepts, LLM integration patterns, or RAG architecture is preferred.

Desired Skills:ย ย ย 

  • Strong proficiency in Python, including experience with FastAPI, pandas, scikit-learn, and async programming patterns.
  • Solid working knowledge of SQL and experience with relational databases (PostgreSQL preferred, Oracle experience a plus).
  • Experience with cloud platforms, primarily AWS (ECS, S3, SQS, Lambda, CloudWatch, Bedrock).
  • Familiarity with ML experiment tracking, model versioning, and MLOps workflows (MLflow preferred).
  • Proficiency with approaches to statistical analysis, mathematical modeling, and data visualization.
  • Experience creating and deploying AI Agents to production using Agentic Libraries and platforms
  • Knowledge of Infrastructure as Code (Terraform), containerization (Docker), and CI/CD pipelines (GitLab).
  • Experience with observability tools (OpenTelemetry, CloudWatch, structlog) for production ML systems.
  • Familiarity with document intelligence, and multimodal AI capabilities.

Soft Skills:

  • Strong analytical and problem-solving abilities with the capacity to operate across ambiguity.
  • Excellent communication skills, including the ability to present complex technical results to executive and non-technical audiences.
  • Self-directed learner comfortable rapidly adopting emerging AI/ML technologies and frameworks.
  • Collaborative mindset suited to cross-functional, agile team environments.
  • Intellectual curiosity about logistics, supply chain, and freight management domain problems.

Additional Information:

Location:

Atlanta, Georgia (Hybrid)

Reports To:

Data Science Manager

Team:

AI and Data Science Team (cross-functional: developers, architects, data scientists, scrum master, DBA)

Methodology:

Agile / Scrum with PI Planning cadence

Key Tools:

Databricks, Python, AWS, Claude API, FastAPI, Playwright, MLflow, Terraform, Docker, GitLab, SageMaker

ย 

ย IntelliTrans supports workforce diversity and is a committed equal opportunity. / Affirmative action employer.