Top Machine Learning Jobs in Des Moines, IA

The Principal Product Manager will lead the Underwriting team to improve credit risk models, manage vendor relationships, and analyze portfolio performance.

The Staff Research Scientist will conduct AI research, innovate in LLM and information retrieval, and collaborate with research teams.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

As a PhD Systems & AI/ML Research Intern, you'll work on infrastructure problems, build prototypes, run benchmarks, and document findings.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Lead the development of audit practices, enhance methodologies, integrate data analytics, ensure compliance, mentor teams, and communicate effectively with leadership.

Manage global technical support teams for MongoDB, focusing on customer satisfaction through technical issue resolution, performance enhancement, and team development.

Lead the development of machine learning systems for Cedar's Personalization Engine, focusing on ML modeling, MLOps, and team management to drive healthcare solutions.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Lead a team of ML engineers to develop computer vision models, manage ML roadmaps, and improve product functionalities through innovative technologies.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Data Architect II, you will design and deliver data solutions, engage stakeholders, and innovate data architecture to support business growth at Hagerty.

The Digital Inside Sales Specialist will identify and close digital transformation opportunities in AI, ML, and automation, focusing on B2B sales within targeted accounts while collaborating with internal teams for technical consultation.

Develop and implement messaging and positioning for AI products, create marketing content, lead go-to-market strategies, and analyze market research.

Lead the development and execution of ML platform strategies, manage a high-performing team, and enhance 3D deep learning applications.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

The Director, Genomics Data will lead genomic data R&D, managing a team to advance data analysis, platform design, and commercialization efforts.

This role involves designing and building advanced ML models to protect against fraud and enhance user experience while mentoring lower-level engineers and influencing technical roadmaps.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

Lead mobile app attribution strategies, collaborating with teams across engineering and data analytics to optimize performance and feature implementation.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The role involves leading AI and data science initiatives, overseeing technical execution, fostering team development, and partnering with stakeholders to drive strategy.