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 ...
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 ...
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$70K - $140K/yr
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Urbandale, IA · On-site
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Eager to solve problems in the autonomous robotics and AI space that have never been solved after. * Passionate about artificial intelligence, machine learning, robotics, autonomy, and automation.
Quick apply
Eager to solve problems in the autonomous robotics and AI space that have never been solved after. * Passionate about artificial intelligence, machine learning, robotics, autonomy, and automation.
Join Workiva as a Sr Machine Learning Engineering Manager - AI Quality and Governance and help establish how we build, evaluate, release, and operate trustworthy AI products at scale. You will lead a ...
Join Workiva as a Sr Machine Learning Engineering Manager - AI Quality and Governance and help establish how we build, evaluate, release, and operate trustworthy AI products at scale. You will lead a ...
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Quick apply
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Quick apply
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New
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New
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Machine Learning Ai Intern information
See Ames, IA salary details
$24.9K - $30.5K
5% of jobs
$32.4K is the 25th percentile. Wages below this are outliers.
$30.5K - $36.1K
59% of jobs
$36.1K - $41.6K
9% of jobs
$42.1K is the 75th percentile. Wages above this are outliers.
$41.6K - $47.2K
17% of jobs
$47.2K - $52.7K
4% of jobs
$52.7K - $58.3K
2% of jobs
$58.3K - $63.9K
3% of jobs
$63.9K - $69.4K
0% of jobs
$69.4K - $75K
0% of jobs
$75K - $80.5K
0% of jobs
$80.5K - $86.1K
0% of jobs
$24.9K
$41.7K
$86.1K
How much do machine learning ai intern jobs pay per year?
What does a Machine Learning AI Intern do?
What types of projects do Machine Learning AI Interns typically work on during their internship?
What are the key skills and qualifications needed to thrive as a Machine Learning AI Intern, and why are they important?
What is the difference between Machine Learning Ai Intern vs Data Science Intern?
| Aspect | Machine Learning Ai Intern | Data Science Intern |
|---|---|---|
| Required Credentials | Relevant coursework, programming skills, basic understanding of ML concepts | Statistics, programming, data analysis skills, often with similar educational background |
| Work Environment | Tech companies, startups, research labs focusing on AI/ML projects | Variety of industries including finance, healthcare, tech, focusing on data analysis |
| Employer & Industry Usage | Primarily in AI/ML development teams within tech and research sectors | Across 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
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
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
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Own the ML model lifecycle: training pipelines, model registry, deployment, monitoring, and guardrails
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Build and maintain CI/CD for ML - automated testing, evaluation, and promotion of models across environments
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Drive observability across AI services: latency tracking, drift detection, cost monitoring, alerting
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Establish SLOs/SLIs for AI services and lead incident response for ML-related production issues and maintain high service availability
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Reduce complexity through simplification, automation, and thoughtful system design
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Lead and grow an existing strong team of machine learning engineers
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Provide hands-on coaching, performance feedback, and growth opportunities for engineers at varying experience levels
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Foster a collaborative, inclusive, and high-ownership team culture grounded in trust, accountability, and continuous improvement
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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
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Communicate complex technical issues to both technical and non-technical audiences effectively
Technical Strategy & Execution
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Manage integrations with frontier model providers (AWS Bedrock, Azure OpenAI, Google) including model routing, load balancing, and fallback strategies
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Drive AI analytics dashboards that give leadership and product visibility into platform health and usage
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Drive improvements in latency, service availability, developer experience, and integration usability across internal and external interfaces
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Guide architectural decisions to ensure platform scalability, reliability, and alignment with Workiva's long-term technical vision
What You'll Need
Minimum Qualifications
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Bachelor's degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience
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7+ years of total experience in software engineering and/or Machine Learning, with at least 2 years of dedicated experience as an Engineering Manager
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Experience with ML pipeline orchestration tools (ClearML, Kubeflow, Airflow, or similar)
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Hands-on background with Kubernetes, microservices, container orchestration, and infrastructure-as-code
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Track record of improving reliability/availability metrics for production ML systems
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Proven ability to manage senior individual contributors, resolve technical conflicts, and build a culture of psychological safety and high performance
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Solid leadership skills in an Agile/Sprint working environment
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Experience operating production ML systems in cloud environments (AWS, Azure, or GCP)
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Master's degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience
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Experience with core concepts of Generative AI such as RAG, Agentic frameworks, etc
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Experience building model evaluation or quality measurement systems
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Familiarity with cost optimization for GPU/model serving workloads
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Familiarity with observability tooling (Datadog, Prometheus, Grafana)
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Willingness to travel up to 15% for team and corporate meetings, fostering relationships and representing company interests
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Reliable internet access for remote working opportunities
How You'll Be Rewarded
Salary range in the US: $163,000.00 - $290,000.00A 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.
#LI-MJ2About Workiva
Sourced by ZipRecruiter
Industry
Software development
Company size
1,001 - 5,000 Employees
Headquarters location
Ames, IA, US
Year founded
2008