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Machine Learning Ai Intern Jobs in Ames, IA (NOW HIRING)

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

... machine learning, NLU and NLP, retrieval-based systems, LLMs, orchestration patterns, tool use, and agentic AI approaches * Demonstrated architectural judgment and ability to make and defend ...

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Data Engineer

Ankeny, IA · On-site

$108K - $130K/yr

Prepares and structures data to support AI and machine learning use cases, including feature-ready datasets, retrieval-augmented generation (RAG) pipelines, and vector embedding storage. * Manages ...

... your learning experience through additional internship seasons Why Join Workiva Workiva is the ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

... your learning experience through additional internship seasons Why Join Workiva Workiva is the ... Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation ...

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Machine Learning Ai Intern information

See Ames, IA salary details

$24.9K

$41.7K

$86.1K

How much do machine learning ai intern jobs pay per year?

As of Sep 12, 2026, the average yearly pay for machine learning ai intern in Ames, IA is $41,655.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,800.00 and $45,000.00 per year, depending on experience, location, and employer.

What does a Machine Learning AI Intern do?

A Machine Learning AI Intern assists in developing, testing, and deploying machine learning models and algorithms under the supervision of experienced data scientists or engineers. Typical responsibilities include data preprocessing, feature engineering, model evaluation, and documentation. Interns may also help in researching new AI techniques and supporting the integration of models into existing applications. The role provides hands-on experience with machine learning tools, programming languages like Python, and frameworks such as TensorFlow or PyTorch. This internship helps build foundational skills for a career in artificial intelligence and data science.

What types of projects do Machine Learning AI Interns typically work on during their internship?

As a Machine Learning AI Intern, you can expect to work on real-world projects such as developing predictive models, performing data preprocessing and analysis, or contributing to the improvement of existing algorithms. Interns often assist with tasks like data cleaning, feature engineering, and model evaluation, while collaborating closely with data scientists and engineers. This hands-on experience helps interns build practical skills and gain exposure to the entire machine learning workflow in a professional setting.

What are the key skills and qualifications needed to thrive as a Machine Learning AI Intern, and why are they important?

To thrive as a Machine Learning AI Intern, you need a solid foundation in mathematics, programming (often Python), and machine learning concepts, usually supported by coursework or relevant projects. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Curiosity, problem-solving ability, and strong communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills are crucial for contributing meaningfully to projects, adapting to new technologies, and growing within the fast-evolving AI field.

What is the difference between Machine Learning Ai Intern vs Data Science Intern?

AspectMachine Learning Ai InternData Science Intern
Required CredentialsRelevant coursework, programming skills, basic understanding of ML conceptsStatistics, programming, data analysis skills, often with similar educational background
Work EnvironmentTech companies, startups, research labs focusing on AI/ML projectsVariety of industries including finance, healthcare, tech, focusing on data analysis
Employer & Industry UsagePrimarily in AI/ML development teams within tech and research sectorsAcross industries for data analysis, reporting, and decision-making support

Machine Learning Ai Interns focus on developing and applying AI and ML models, often working closely with data scientists and engineers. Data Science Interns work on analyzing data, creating reports, and supporting data-driven decisions. While both roles require programming and analytical skills, ML Interns typically specialize in AI algorithms, whereas Data Science Interns focus on broader data analysis tasks.

Manager of Machine Learning - AI Modeling and Operation

Ames, IA • On-site

Workiva, Inc.
Software Development • 1 - 5K employees

Other

Retirement

This job post has expired today. Applications are no longer accepted.


Key responsibilities

  • Own the ML model lifecycle, including training pipelines, model registry, deployment, monitoring, and guardrails

  • Build and maintain CI/CD processes for ML, including automated testing, evaluation, and model promotion

  • Manage integrations with frontier model providers, including model routing, load balancing, and fallback strategies


Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz


Job description

Join our team at Workiva as an Manager of Machine Learning - AI Modeling and Operation! As a pivotal member of our AI/ML team, you'll own the infrastructure that makes every AI feature at Workiva reliable, observable, and deployable.

You will lead the team responsible for ML infrastructure, model operations, and AI quality at Workiva. Your team owns the systems that make AI reliable in production from model lifecycle management to evaluation frameworks, observability, and model routing across frontier providers. You'll build the operational backbone that every AI feature at Workiva depends on.

Join us if you want to own the infrastructure layer that makes enterprise AI work at scale, not just build demos. Discover more about Workiva's Generative AI.

What You'll Do

Operational Excellence

  • Own the ML model lifecycle: training pipelines, model registry, deployment, monitoring, and guardrails

  • Build and maintain CI/CD for ML - automated testing, evaluation, and promotion of models across environments

  • Drive observability across AI services: latency tracking, drift detection, cost monitoring, alerting

  • Establish SLOs/SLIs for AI services and lead incident response for ML-related production issues and maintain high service availability

  • Reduce complexity through simplification, automation, and thoughtful system design

Leadership & Team Management
  • Lead and grow an existing strong team of machine learning engineers

  • Provide hands-on coaching, performance feedback, and growth opportunities for engineers at varying experience levels

  • Foster a collaborative, inclusive, and high-ownership team culture grounded in trust, accountability, and continuous improvement

Cross Functional Collaboration
  • Partner with Intelligence pillar engineering squads (AGFW, AIEI, AIQG, Applied AI, Search) and Product teams to ensure AI services are production-ready, operationally sound, and observable

  • Communicate complex technical issues to both technical and non-technical audiences effectively

Technical Strategy & Execution

  • Manage integrations with frontier model providers (AWS Bedrock, Azure OpenAI, Google) including model routing, load balancing, and fallback strategies

  • Drive AI analytics dashboards that give leadership and product visibility into platform health and usage

  • Drive improvements in latency, service availability, developer experience, and integration usability across internal and external interfaces

  • Guide architectural decisions to ensure platform scalability, reliability, and alignment with Workiva's long-term technical vision

What You'll Need

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience

  • 7+ years of total experience in software engineering and/or Machine Learning, with at least 2 years of dedicated experience as an Engineering Manager

  • Experience with ML pipeline orchestration tools (ClearML, Kubeflow, Airflow, or similar)

  • Hands-on background with Kubernetes, microservices, container orchestration, and infrastructure-as-code

  • Track record of improving reliability/availability metrics for production ML systems

  • Proven ability to manage senior individual contributors, resolve technical conflicts, and build a culture of psychological safety and high performance

  • Solid leadership skills in an Agile/Sprint working environment

  • Experience operating production ML systems in cloud environments (AWS, Azure, or GCP)

Preferred Qualifications
  • Master's degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience

  • Experience with core concepts of Generative AI such as RAG, Agentic frameworks, etc

  • Experience building model evaluation or quality measurement systems

  • Familiarity with cost optimization for GPU/model serving workloads

  • Familiarity with observability tooling (Datadog, Prometheus, Grafana)

Working Conditions
  • Willingness to travel up to 15% for team and corporate meetings, fostering relationships and representing company interests

  • Reliable internet access for remote working opportunities

How You'll Be Rewarded

Salary range in the US: $163,000.00 - $290,000.00

A discretionary bonus typically paid annually

Restricted Stock Units granted at time of hire

401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world's most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation-ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.

At Workiva, you'll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you're energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we'd love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email talentacquisition@workiva.com.

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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What Workiva employees say

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