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Machine Learning Engineer Jobs in Iowa (NOW HIRING)

Workiva, Inc.

Staff Machine Learning Engineer

Ames, IA · On-site +1

Join our team at Workiva as a Staff Machine Learning Engineer! As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and delivery of groundbreaking machine learning ...

Workiva, Inc.

Staff Machine Learning Engineer

Ames, IA · On-site

Join our team at Workiva as a Staff Machine Learning Engineer! As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and delivery of groundbreaking machine learning ...

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$29.6K

$120.9K

$181.7K

How much do machine learning engineer jobs pay per year?

As of Jun 7, 2026, the average yearly pay for machine learning engineer in Iowa is $120,948.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $145,600.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
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What are popular job titles related to Machine Learning Engineer jobs in Iowa? For Machine Learning Engineer jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Iowa look for? The top searched job categories for Machine Learning Engineer jobs in Iowa are:
What cities in Iowa are hiring for Machine Learning Engineer jobs? Cities in Iowa with the most Machine Learning Engineer job openings:
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Machine Learning Engineer jobs near you
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Workiva, Inc.

Ames, IA • On-site, Remote

Other

Retirement

Posted 11 days ago

Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

1st of 186 rated software companies

Job description

Join our team at Workiva as a Staff Machine Learning Engineer! As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and delivery of groundbreaking machine learning solutions across our platform. Your expertise will be instrumental in leading projects that demand innovative problem-solving, including the integration of cutting-edge Generative AI into our products.

In this role, you'll have the chance to develop robust tools, systems, and infrastructure to bolster the development, monitoring, and management of our machine learning solutions. Leveraging your engineering prowess, you'll tackle challenges related to availability and scaling, ensuring the long-term stability of our systems.

If you're passionate about pioneering the possibilities of Generative AI and want to be part of a team driving innovation at Workiva, we invite you to join us! Learn more about Workiva's Generative AI and be part of shaping the future of ML with us.

What You'll Do

Architect and Develop Solutions

  • Architect and deliver cutting-edge ML solutions using MLOps and best practices, fostering creativity in project execution

  • Design systems to enable rapid ML development, high availability, and clear observability

  • Develop tools, systems, and automation to support ML solutions, ensuring efficiency, scalability, and rapid development

Collaborate and Lead

  • Collaborate closely with product teams to develop APIs, maintain ML infrastructure, and integrate machine learning features into products

  • Provide technical leadership, mentor less experienced ML engineers and scientists, and define team best practices and processes

  • Lead in the ML space by introducing new technologies and techniques, and applying them to Workiva's strategic initiatives

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

  • Collaborate with software, data architects, and product managers to design complete software products that meet a broad range of customer needs and requirements

Ensure Reliability and Support

  • Deliver, update, and maintain machine learning infrastructure to meet evolving needs

  • Host ML models to product teams, monitor performance, and provide necessary support

  • Write automated tests (unit, integration, functional, etc.) with ML solutions in mind to ensure robustness and reliability

  • Debug and troubleshoot components across multiple service and application contexts, engaging with support teams to triage and resolve production issues

  • Participate in on-call rotations, providing 24x7 support for all of Workiva's SaaS hosted environments

  • Perform Code Reviews within your group's products, components, and solutions, involving external stakeholders (e.g., Security, Architecture)

What You'll Need

Required Qualifications

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

  • Minimum of 4 years in ML engineering or related software engineering experience

  • Proficiency in ML development cycles and toolsets

Preferred Qualifications

  • Familiarity with Generative AI

  • Strong technical leadership skills in an Agile/Sprint working environment

  • Experience building model deployment and data pipelines and/or CI/CD pipelines and infrastructure

  • Proficiency in Python, GO, Java, or relevant languages, with experience in Github, Docker, Kubernetes, and cloud services

  • Proven experience working with product teams to integrate machine learning features into the product

  • Experience with commercial databases and HTTP/web protocols

  • Knowledge of systems performance tuning and load testing, and production-level testing best practices

  • Experience with Github or equivalent source control systems

  • Experience with Amazon Web Services (AWS) or other cloud service providers

  • Ability to prioritize projects effectively and optimize system performance

Working Conditions

  • Less than 10% travel

  • Reliable internet access for remote working opportunities

How You'll Be Rewarded

Salary range in the US: $163,000.00 - $261,000.00

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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