Top Machine Learning Jobs in Des Moines, IA

Leads ExtraHop’s product marketing function, including team leadership, portfolio positioning, messaging, product launches, competitive analysis, sales enablement, content development, integrated campaigns, and executive-level customer and industry engagement. The role requires deep cybersecurity and enterprise technology expertise, strong storytelling and technical communication skills, and collaboration across product, sales, marketing, and partner teams.

Own a broad territory focused on acquiring net-new enterprise customers for SingleStore’s AI and data platform. Build self-sourced pipeline through outbound, account-based, partner, and market-education motions; engage executive and technical stakeholders; develop ROI and TCO cases; navigate complex technical, security, legal, procurement, and negotiation processes; partner with engineers to establish production workloads; and manage forecasting, qualification, CRM hygiene, and new-logo performance.

Drives growth by identifying strategic partnerships with enterprise AI and machine learning companies. Develops business development strategies, builds relationships with senior decision-makers, negotiates complex deals, and collaborates with internal teams to implement partnerships. Requires strong AI/ML industry knowledge, executive communication skills, strategic thinking, and adaptability in a fast-paced startup environment.

Leads cross-functional programs that improve products, customer support, and value delivery. Owns execution, coordinates engineering and operations teams, establishes scalable processes, uses data-driven insights to improve customer models, scopes and sequences major initiatives, and communicates progress to stakeholders. The role requires program management experience, strong communication and influence skills, comfort with ambiguity, rapid execution in scaling environments, and interest in AI systems.

Conduct hands-on research with frontier AI labs to evaluate model behavior, identify failure modes, and design interventions that improve reliability. Responsibilities include designing evaluations, building data pipelines and fine-tuning workflows, collaborating with internal and external stakeholders, and addressing challenges involving long-context reasoning, tool use, and real-time feedback loops.

Manages strategic client accounts for an AI data platform, serving as the primary customer contact and trusted advisor. Oversees data projects, SLAs, quality, and deliverables while coordinating engineering, operations, and project teams. Builds strong client relationships, addresses concerns, translates AI and NLP requirements into actionable plans, and ensures solutions meet customer goals.

Lead finance-focused AI training, evaluation, and data programs across financial analysis, equity research, credit assessment, regulatory compliance, and quantitative modeling. Serve as the finance subject-matter expert, establish quality frameworks, coordinate cross-functional teams, manage timelines, and translate financial expertise for AI/ML teams and financial-services clients.

Lead customer-centric product development and strategic initiatives for an AI platform. Responsibilities include understanding customer pain points, overseeing product and operations execution, managing accounts, building scalable systems and processes, coordinating with engineering, analyzing performance data, and driving product insights through market and competitive research.

Forward Deployed Engineers embed with customers to identify operational problems, analyze imperfect data, rapidly prototype and deploy AI-powered solutions, and drive adoption. Responsibilities include building pipelines, models, dashboards, optimizers, agents, and operational applications; collaborating with stakeholders; training users; improving platform capabilities; and supporting follow-on customer opportunities. The role requires technical execution, product thinking, client partnership, commercial awareness, and significant travel.

Leads data and analytics transformation strategy for major client programs, defining roadmaps, use cases, architecture direction, and operating models. Advises senior stakeholders, facilitates strategy workshops, aligns programs to KPIs and value frameworks, supports governance and risk management, contributes to proposals and pre-sales, and mentors consulting and analytics teams.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Own machine learning models end to end, from data preparation and training through evaluation and production deployment. Build pipelines for large multimodal datasets including video, sensor streams, and language. Collaborate with engineering and computer vision teams, rapidly prototype solutions, apply relevant research, and continuously improve production models and tooling.

Source, develop, and close enterprise health system clients across a US territory. Build relationships with healthcare executives, launch and expand pilot programs, create account plans, meet revenue targets, and transition customers to Client Success. Collaborate with product, legal, marketing, support, and leadership; provide sales forecasts and pipeline reporting in HubSpot; influence the product roadmap; and represent Nabla at industry events.

Develop and launch scalable, user-facing features for AI-powered video and multimedia tools. Architect end-to-end solutions across backend and frontend systems, ensure quality and reliability, collaborate with design, product, and ML teams, and mentor engineers. The role involves rapid prototyping, experimentation, technical leadership, and shaping Pika’s core creative product.

Conduct applied AI and machine learning research for semiconductor testing. Define ambiguous technical problems, develop measurable evaluation methods, build and fine-tune models, and create RAG, knowledge-graph, and agent systems. Translate unstructured tester documentation and protocols into production solutions, collaborate with engineering and domain experts, and deploy tools that improve workflows. The role also requires monitoring emerging AI technologies and proposing new research directions.

Lead the technical direction and hands-on development of ML and operations research systems powering delivery dispatch. Build pricing, quote selection, forecasting, routing, batching, fleet recommendation, LLM, optimization, evaluation, and MLOps capabilities. Translate operational constraints into reliable models and solver formulations, establish production ML standards, and mentor engineers. The role partners with Product and leadership to deliver measurable improvements in revenue, margin, utilization, conversion, and delivery reliability.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead Tilt’s product design function across consumer financial products. Set design vision and quality standards, manage and grow a team of six designers and one researcher, build research capabilities, influence product strategy, scale the design system, advocate for users, and partner with Product, Engineering, Marketing, and executive leadership. Drive AI-enabled design practices and ensure product experiences deliver measurable user and business impact.

Manage strategic enterprise accounts, building executive relationships, developing multi-year account plans, driving retention, expansion, upsell and cross-sell opportunities, and closing complex technology deals. Coordinate cross-functional Basis teams, lead executive business reviews, align customer priorities with company objectives, and represent Basis at customer and industry events.

Own the strategy, roadmap, and growth of Ottimate’s new product initiatives across procurement, budgeting, spend planning, and contract management. Lead customer discovery, validation, MVP development, launches, and portfolio metrics. Manage product managers and designers, oversee Design and UX, and partner with engineering, data science, sales, marketing, and customer success to deliver coherent, market-ready products.

Owns and grows strategic Financial Services accounts by prospecting, developing channel and alliance opportunities, presenting cybersecurity solutions, closing new business, and expanding customer relationships. The role requires enterprise technology and security sales expertise, executive engagement, account planning, forecasting, reseller collaboration, and the ability to explain NDR, Agentic SOC, AI security, and network visibility solutions. Travel is primarily remote and on the road, with at least 50% travel required.

Build and scale production AI systems for Prophetic’s real estate intelligence platform. Responsibilities include developing agentic systems, data pipelines, inference workflows, evaluation benchmarks, geospatial processing, and machine learning applications across hundreds of millions of records. The role requires shipping reliable Python services, optimizing throughput and cost, integrating research into products, and collaborating with engineering and product teams.

Designs integration architecture for third-party agentic AI tools within secure, vendor-isolated government enclaves. Defines data packages, identity federation, tenant isolation, audit logging, and PHI/PII governance. Provides hands-on expertise in LLMs, RAG, fine-tuning, tool use, multi-agent orchestration, and LLMOps. Guides AWS and Databricks-based AI/ML deployments, evaluation, monitoring, and automation while presenting architectures to technical and non-technical stakeholders.

Lead development and deployment of predictive and ML models for credit risk, collections, and operations. Mentor data scientists, promote MLOps and modern tools, present insights to stakeholders, and drive experimentation with techniques such as causal inference and GenAI.

Develop and deploy machine learning models and production software for multi-object tracking in autonomous trucks. Responsibilities include sensor fusion across camera, LiDAR, and radar; scalable PyTorch training workflows; tracking algorithm development; large-scale data analysis; C++ and Python engineering; safety and validation strategy; architecture decisions; and cross-functional collaboration. The role also provides technical leadership through design reviews, code reviews, mentoring, and engineering best practices.