Top Machine Learning Jobs in Des Moines, IA

Own and modernize Apartment List’s B2C lifecycle marketing program across email, push, and SMS. Build segmentation, personalization, partnerships, cross-sell, forecasting, experimentation, and measurement systems. Lead analytics and hands-on journey development, audience logic, troubleshooting, and SQL analysis. Manage and develop a two-person team, oversee the Iterable relationship, and partner with Engineering, Product, Analytics, Design, and senior leadership to drive renter engagement, retention, revenue, and marketplace growth.

Provides senior functional and technical leadership for NetSuite and connected financial systems. Partners with Finance, Accounting, and technology teams to design processes, configure NetSuite, manage integrations, protect close-cycle continuity, support production incidents, implement controls, coordinate releases, and deliver testing and documentation. The role also leads automation initiatives, vendor engagement, solution lifecycle delivery, and mentorship while supporting accounting, compliance, reporting, and multi-entity financial operations.

Staff Software Engineer responsible for setting technical direction, architecting scalable distributed systems, shipping high-impact features, and building AI-powered tools for a virtual healthcare platform. The role includes mentoring engineers, partnering with product and clinical leadership, translating user needs into technical solutions, and guiding frontend and backend application development in a fast-paced startup environment.

Lead mainframe modernization and migration architecture for large global clients. Conduct discovery workshops, assess legacy environments, develop transformation and re-platforming solutions, present technical business cases, and advise executives. Partner with sales, consulting, operations, product management, and clients to create solutions, influence technology roadmaps, drive stability and innovation, and support complex opportunities. The role requires deep mainframe expertise across legacy languages, databases, operating systems, infrastructure, and modernization technologies.

Leads enterprise evaluation, governance, and implementation planning for emerging mental health therapeutics, including digital therapeutics, AI-enabled tools, neuromodulation, pharmacotherapies, and technology-enabled care models. Develops clinical protocols, workflows, provider training, safety criteria, outcome measurement, and adoption support. Partners with clinical, technology, research, quality, operations, and growth teams; evaluates vendors and evidence; monitors regulatory developments; and advances responsible innovation across the organization.

Design and deploy production machine learning models and conversational AI agents that transform advertiser briefs into optimized media plans. Build evaluation systems to improve model and agent quality, collaborate across science and engineering teams, investigate ambiguous problems, and iterate using performance data and seller feedback. Communicate effectively with technical and non-technical stakeholders while contributing broadly across machine learning domains.

Leads end-to-end customer onboarding and implementation programs, translating customer goals into project plans, milestones, dependencies, risks, and success metrics. Coordinates Sales, Product, Engineering, Support, Customer Success, trainers, and subject-matter experts without performing hands-on technical implementation or training. Establishes scalable operational frameworks, manages cross-functional accountability, oversees technical readiness, tracks adoption, facilitates stakeholder communications, and ensures customers are prepared for go-live.

Own the full sales cycle across North America, including prospecting, pipeline generation, client meetings, contract negotiation, and closing new business. Build markets across eCommerce, fintech, real-money gaming, and mobile apps while partnering with Customer Success, Marketing, and Product. Represent the company at industry events, monitor mobile advertising trends, and achieve personal and regional revenue targets exceeding $1 million annually.

Lead the roadmap and delivery of an AI-native L1 IT operations agent. Partner with customers, design partners, engineering, and go-to-market teams to ship enterprise-scale capabilities, improve self-service adoption, and build trust through transparent agent experiences and feedback loops. Drive product strategy from discovery through launch in a fast-paced, ambiguous environment.

Owns P&L performance, profitability, growth, and digital transformation for Small and Lower Mid-Market commercial insurance portfolios. Leads pricing, underwriting, portfolio monitoring, analytics, data visualization, predictive modeling, and machine learning initiatives. Partners with actuarial, product, engineering, technology, and distribution teams to implement process improvements and underwriting actions across digital channels and geographies. Communicates insights to stakeholders and senior leadership while leading cross-functional teams in an Agile operating model.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Provides safe, therapeutic perioperative nursing care using the nursing process. Performs assessment, planning, implementation, and evaluation; scrubs and circulates for complex spine and orthopedic surgeries; supports interdisciplinary teams; and assists with managing care delivered by other nursing staff. Requires California RN licensure, CPR certification, and substantial adult operating room experience, including spine procedures. Must work across UCSF Health locations and function effectively under pressure.

Build and deploy advanced machine learning and agentic AI systems that improve Airbnb’s customer service experience. Responsibilities include developing AI assistants, integrating ML products, optimizing model performance, applying LLM techniques such as fine-tuning and RAG, building multi-agent architectures, and shipping scalable production ML systems. The role collaborates closely with Engineering, Product, and Design teams and contributes to emerging AI initiatives from concept through production.

Develop and validate machine learning models, training pipelines, inference systems, and numerical methods using Python. Debug algorithmic and system-level issues, optimize memory usage and performance, design systematic tests, and build reproducible workflows. Review challenging ML engineering tasks, use coding agents in development, document technical findings, and deliver high-quality work independently within deadlines.

Owns architecture and technical standards for AI/ML platforms, agent frameworks, MCP integrations, orchestration, context engineering, evaluation, governance, and human approval controls. The role guides AI engineers, mentors technical teams, reviews complex designs, and partners with platform, data, network, and UI/UX engineering groups. Responsibilities include production readiness, secure development, monitoring, retrieval systems, tool safeguards, auditability, and enterprise adoption of emerging AI technologies.

Develop and optimize generative AI architectures for material and molecular discovery, including diffusion models, flow matching, and GFlowNets. Integrate reward signals from learned predictors and simulations, manage data ingestion and quality control, develop computational workflows, and deploy production-grade ML capabilities. Collaborate with ML researchers, computational scientists, engineering, product, and R&D teams. The role requires expertise in applied ML, scalable frameworks, cloud platforms, and material discovery, with preferred experience in active learning, Bayesian optimization, guided generation, and agentic or LLM methods.

Develop and deploy machine-learned interatomic potentials for PFAS substitution. Responsibilities include generating and curating first-principles training data, building reproducible cloud and HPC workflows, training and validating ML force fields, running molecular dynamics and quantum chemistry campaigns, predicting physical properties, extending models to condensed-phase and process chemistries, and communicating model uncertainty and domain limitations.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

Leads the AI product strategy and roadmap, extending governed Alteryx workflows and business logic into enterprise AI agents and LLM ecosystems. Owns the Faster, Better, Cheaper ROI narrative, benchmarks product performance, quantifies customer value, champions trustworthy AI through the VURA framework, and represents the product vision with customers, analysts, and external audiences.

Own the enterprise architecture vision for scalable, high-performance, cost-efficient multi-tenant SaaS systems. Lead AWS cloud optimization, distributed data and AI infrastructure, architectural governance, and Architecture Review Council activities. Guide engineering teams on microservices, event-driven systems, automation, and cloud-native practices while driving GenAI adoption across the software lifecycle. Build prototypes, establish architectural standards, optimize total cost of ownership, and mentor technical leaders.

Leads Dandelion Health’s AI developer business by building pipeline, closing clinical AI data and validation partnerships, recruiting developers into its marketplace, and achieving revenue targets. Develops commercial strategy, manages executive relationships, structures agreements, and collaborates with marketing, product, data, engineering, and clinical informatics teams. Represents the company at industry events and advises on clinical AI validation, regulatory, payer, and competitive dynamics.

Researches, develops, tests, and maintains materials-aware machine learning models and software. Designs scalable ML systems, improves model interpretability and uncertainty quantification, and develops inverse-design capabilities. Collaborates with product, engineering, and external research teams to deliver customer-focused AI solutions, publishes research, reviews code, analyzes model performance, and mentors developers.

Develop and deploy machine learning algorithms that improve real-time device identification and fraud detection. Own data science projects from experimentation through production, including supervised, semi-supervised, and unsupervised learning, real-time inference, training automation, exploratory analysis, and model-to-service integration. Contribute to engineering best practices, collaborate within a global remote team, and participate in a shared on-call rotation.

Develop, optimize, and deploy production-grade computer vision and deep learning models for real-time perception and navigation on edge hardware. Integrate AI systems with robots, drones, unmanned systems, and swarms while optimizing inference with CUDA and TensorRT. Manage containerized deployments using Docker and Kubernetes, contribute to CI/CD and automated testing, and transition research prototypes into reliable production features.