Top Machine Learning Jobs in Des Moines, IA

Lead development and productionization of large-scale ranking and personalization ML systems. Build data pipelines, features, and models (batch and real-time), collaborate cross-functionally, run experiments, and improve infrastructure for search, recommendation, and marketplace optimization.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Lead and scale full-stack engineering teams for Yahoo Mail; define engineering vision and roadmap; drive AI-native development and AI transformation using Generative AI/LLMs and agents; partner with Product, Design, and Data Science to deliver scalable cloud-native mobile and web experiences; hire, mentor, and retain engineering talent while guiding architecture, technical reviews, and platform modernization.

Design, build, test, deploy, and maintain production AI capabilities (agents, workflows, models, MCP servers, APIs) across a SaaS dental platform. Train and operate ML models, implement RAG and vector DB solutions, use AI-assisted tools, collaborate in design and code reviews, and support production reliability and monitoring.

Design, optimize, and operate production LLM inference and training pipelines. Improve latency, throughput, and GPU utilization using techniques like batching, quantization, FlashAttention, and kernel-level profiling. Deploy and autoscale multiple models on shared GKE GPU clusters, consult with clients on performance and cost requirements, and carry prototypes to robust, scalable production services.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The Senior Product Architect will design security products, collaborating with product management and engineering teams, focusing on architecture and functionality for high-level product features.

The Vice President of Underwriting will lead the company's underwriting strategy, focusing on growth acceleration while managing credit, fraud, regulatory, and reputational risks. This role involves overseeing underwriting processes, implementing advanced analytics, optimizing risk frameworks, and ensuring regulatory compliance across different merchant segments.

Transfyr seeks adaptable builders for various roles across CS, biology, and business. Responsibilities include developing sensor stacks, data harmonization, computer vision, machine learning systems, lab operations, project management, and business development.

The Vice President of AI will define and lead the AI strategy at Tempo, integrating AI capabilities into products, building teams, and ensuring ethical use of AI while driving business outcomes and customer value.

The Product Counsel Senior Director provides legal counsel on product development and AI, manages IP portfolios, oversees compliance, and advises on technology transactions.

Lead a team of advanced product analysts, conduct data analysis and statistical modeling, design experiments, and develop reporting tools to drive product decisions and business performance.

Lead federal sales engineering efforts: deliver tailored demos, respond to federal RFPs/RFIs, navigate agency security reviews and ATO processes, produce solution designs aligned to federal frameworks (FedRAMP, NIST), and advise product/GT M strategy for federal use cases in fraud, identity, and AML.

Design, develop, and deploy end-to-end AI/ML applications (RAG, chatbots, agentic workflows). Build scalable data pipelines, apply graph analytics, entity resolution, and NLP for risk scoring, anomaly detection, and investigative prioritization. Develop models, REST APIs, and deploy/manage solutions in AWS to support federal mission use cases.

Provide commercial legal support across Sales, Product, Partnerships, Procurement, and Engineering: draft and negotiate NDAs, SaaS and vendor agreements, advise on product and privacy/regulatory risks (GDPR, CCPA/CPRA, GLBA), improve contract lifecycle management, and respond to day-to-day legal inquiries and ad hoc projects.

Build and re-architect Shipt's LLM-native search stack including retrieval and ranking systems. Design multi-task and multi-objective models, integrate personalization signals, develop hybrid dense/sparse retrieval, and apply generative retrieval and query expansion. Analyze search data, report findings to leadership, and partner with senior scientists and ML engineers to improve relevance, revenue trade-offs, and operational metrics.

Support development of pricing arrangements, financial models, budgets and AFAs for a law firm. Produce pricing analyses, competitive market research, and performance metrics. Collaborate with attorneys, IT, and data teams to implement pricing tools (Elite 3E, Iridium), leverage AI/analytics for forecasting, and train stakeholders on pricing technology.

Lead and grow the AI Forward Deployed Engineering team, oversee customer AI/ML transformations, and develop strategic partnerships while managing key accounts.

Develop and scale reinforcement-learning systems that close the loop between automated labs and reward models. Build synthetic data engines and inference infrastructure for large-scale training, maintain evaluations of learned policies using proprietary experimental datasets, and address real-world challenges like experimental noise and expensive queries.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

As a Senior Staff Machine Learning Engineer, you will lead the development and deployment of machine learning models, ensuring they drive business growth and meet performance requirements. You will collaborate with teams, manage data pipelines, and implement state-of-the-art solutions while continuously improving model performance.

The role involves developing and deploying machine learning models for forecasting within the Camus platform, requiring collaboration and technical depth in ML.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.