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Python Ml Developer Jobs in Iowa (NOW HIRING)

Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models

Data Architect

West Des Moines, IA ยท On-site

$58.50 - $75.25/hr

Design logical, physical, and conceptual data models to support analytics, reporting, AI/ML, and ... Collaborate with engineers to implement architectural patterns in production systems * Ensure ...

Senior Data Engineer

Cedar Rapids, IA ยท Hybrid

$95K - $115K/yr

Experience with analytics, ML technologies. * Experience with data visualization tools. * Relevant certifications (AWS, etc.). * Programming experience (DBT, Python, Scala, Node.js). * Snowflake ...

Experience with object-oriented programming using languages such as Java, Python, or JavaScript ... Basic understanding of AI/ML frameworks such as TensorFlow or PyTorch. Compensation The wage range ...

Senior Staff Machine Learning Engineer - US

Ames, IA ยท On-site +1

$112K - $153K/yr

... ML, AI, or data-intensive systems Preferred Qualifications * Experience designing and operating ... Expert-level Python proficiency and proficiency in at least one production language such as Java ...

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Python Ml Developer information

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

What are popular job titles related to Python Ml Developer jobs in Iowa? For Python Ml Developer jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Iowa look for? The top searched job categories for Python Ml Developer jobs in Iowa are:
What cities in Iowa are hiring for Python Ml Developer jobs? Cities in Iowa with the most Python Ml Developer job openings:
Infographic showing various Python Ml Developer job openings in Iowa as of June 2026, with employment types broken down into 92% Full Time, 6% Part Time, 1% Temporary, and 1% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.
Senior Applied Scientist

Senior Applied Scientist

Relativity

Des Moines, IA โ€ข On-site, Remote

Full-time

Medical, Retirement

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy, trust, and accountability are critical. Every year, the global justice system benefits from insights generated by Relativity AI across billions of documents. We are just getting started on our journey to use AI to improve the outcome of every discovery, investigation, and analysis performed on our platform. At Relativity, we develop AI guided by our AI Principles. These principles ensure we build AI with clear purpose, empower customers with transparency and control, treat fairness and privacy as first principles, protect customer data by design, and act with a high standard of responsibility and accountability. WHAT WE DO Relativity's AI organization is focused on exploration, experimentation, and turning cutting-edge research into real-world impact. We believe innovation requires experimentation, learning, and iteration. Our teams experiment, evaluate, ship, and learn continuously while maintaining a strong commitment to responsible AI. Applied Science Team The Applied Science team operates at the core of Relativity's AI development. Our team includes specialists with advanced postgraduate training and deep experience building and operating machine learning models at scale. We work closely with engineering, product, design, data engineering, machine learning operations, and LLM engineering teams to translate complex AI research into production-ready features used by legal professionals around the world.

Job Description and Requirements

ABOUT THE ROLE

As a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and machine learning models that power Relativity's next generation of AI-driven product capabilities. You will collaborate closely with applied scientists, engineers, product managers, and designers to build models that help legal professionals organize data, discover the truth, and act on it with confidence.

This role balances research, development, and operational responsibility. You will contribute to Relativity's portfolio of transformational generative AI technologies while adhering to our responsible AI principles and ensuring models perform reliably in real-world, high-stakes environments.

WHAT YOU'LL DO

  • Develop machine learning and generative AI models that ship as customer-facing product features
  • Collaborate closely with engineers to write production-quality code and contribute across the full model deployment lifecycle
  • Design and evaluate models that operate at very large scale, including search and retrieval systems spanning hundreds of millions to billions of documents
  • Contribute to internal standards, processes, and tooling for building, evaluating, and deploying generative AI systems
  • Partner with Product and Data teams to assemble, curate, and synthesize datasets for model development and evaluation
  • Conduct rigorous experimentation, model evaluation, and iteration to improve model quality, explainability, safety, and performance
  • Collaborate across AI, engineering, and product teams to ensure models integrate effectively into larger systems
  • Apply Relativity's AI Principles to ensure responsible, fair, secure, and transparent AI development
  • Communicate complex data science and machine learning concepts clearly and effectively to collaborators with diverse technical backgrounds

WHAT WE'RE LOOKING FOR

Required

  • Experience building search or retrieval systems operating at the scale of hundreds of millions of documents
  • Experience developing and applying generative AI models as part of larger, domain-specific systems
  • Experience across the full machine learning lifecycle, including experimentation, evaluation, deployment, and iteration
  • Experience working in containerized environments using Kubernetes-based tooling and workflows
  • Interest in or experience with the legal industry, eDiscovery, or the broader justice system
  • Strong programming ability in a language such as Python
  • Comfort working in UNIX-based environments using command-line tools
  • Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders

Preferred

  • Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry experience
  • OR Ph.D. in Computer Science or a quantitative field
  • OR the equivalent of 5 years of relevant academic and/or industry experience
  • Experience building and deploying systems that leverage large language models
  • Experience contributing to shared data science or ML engineering standards, tooling, or best practices

WHY WE COULD BE A GREAT FIT

Impactful Mission

  • Your work directly contributes to improving outcomes across the global justice system by helping customers uncover critical insights in massive, complex datasets.

AI at Real Scale

  • You'll work on some of the largest and most complex AI systems in the legal technology market, operating at significant data and computational scale.

Growth and Collaboration

  • You'll collaborate closely with experienced applied scientists, engineers, and product leaders while continuing to grow your expertise in generative AI and production machine learning systems.

Responsible AI Culture

  • You'll be part of an organization deeply committed to building AI that is ethical, transparent, secure, and accountable.

Inclusive Environment

  • We value diverse perspectives, backgrounds, and ways of thinking, and believe they make our teams and products stronger.

Compensation and Benefits

  • Competitive compensation, health and retirement benefits, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$146,000 and $218,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models