Top Machine Learning Jobs in Cleveland, OH

Onboard new customers, support product deployment, and create playbooks for customer success and new-hire training. The role works closely with the CEO and CSO at a climate technology startup, addressing ambiguous problems and developing innovative solutions for agriculture and energy customers. Experience in customer success or product management is required; agriculture, SaaS, and early-stage startup experience are preferred.

Designs, builds, and evaluates complete AI systems for Pearson’s K-12 assessment platform. Responsibilities include predictive machine learning, statistical methods, retrieval, knowledge graphs, generative and agentic AI, deterministic services, human review, and system integration. The role develops evaluation datasets and regression suites, analyzes failure modes, supports model adaptation, monitors deployed systems, and collaborates with engineers, psychometricians, learning scientists, and content experts to create transparent, reliable, and auditable AI capabilities.

Develops data visualization, analytics, machine learning, and automation solutions for coherent optical product manufacturing. Mines wafer-to-module datasets to identify yield drivers, failure signatures, anomalies, correlations, and process drift. Builds and evaluates ML algorithms for yield prediction and root-cause analysis, performs statistical analysis, and automates engineering workflows using GenAI. Collaborates with R&D, manufacturing, and AI/ML teams to optimize product performance and communicate findings to technical audiences.

Researches, designs, develops, trains, and deploys computer vision and machine learning models. Builds and maintains ML software, testing and validation processes, and documentation. Applies image and video processing, deep learning, and computer vision techniques across edge and cloud-based platforms while improving existing applications and performance.

Build and maintain a full-stack sewer inspection analysis platform using React, TypeScript, Node.js, PostgreSQL/PostGIS, AWS, computer vision, geospatial analysis, and Temporal.io. Responsibilities include developing interactive dashboards, scalable APIs, video-processing workflows, mapping and risk-assessment tools, microservices, cloud infrastructure, and automated testing and deployment pipelines.

Build and optimize technical infrastructure supporting customer operations, trust and safety, and sales workflows. Develop system integrations, automated workflows, internal support tools, AI-powered customer service solutions, dashboards, and reporting systems. Identify operational bottlenecks, improve processes, and collaborate with product, engineering, operations, customer success, and trust and safety teams to scale efficiently.

Own the vision, roadmap, quality standards, and adoption strategy for catalog APIs powering AI commerce experiences. Lead catalog coverage, product identity, enrichment, ingestion, pricing, availability, freshness, data rights, partner onboarding, metrics, and evaluation initiatives. Partner with engineering, applied science, legal, privacy, security, marketing, and external partners to prioritize investments, guide large senior teams, and scale externally consumed commerce data platforms.

Leads global revenue operations strategy and execution across GTM measurement, account planning, pipeline reporting, territory planning, incentives, pricing, forecasting, operating cadences, and technology. Builds AI-enabled workflows, optimizes the HubSpot, ZoomInfo, and Gong stack, drives adoption, and provides actionable insights to leadership and regional sales and marketing teams.

Applied data scientist responsible for solving data-quality and machine-learning problems, evaluating model performance in production, detecting drift, building ground truth, and prototyping data products. The role uses classification, entity resolution, anomaly detection, embeddings, semantic search, feature engineering, statistical analysis, dashboards, and large-scale production data. The scientist works independently within product or data teams and partners with engineers, analysts, product managers, and subject-matter experts.

Leads the team building LTK’s foundational AI platform, including shared models, services, evaluation frameworks, and production LLM capabilities. Responsibilities include setting the AI roadmap, enabling internal engineering and product teams, overseeing deployment and operational performance, managing quality and cost, and establishing evaluation and monitoring practices. The role also involves hiring, coaching, performance management, and developing a high-performing data science and machine learning organization.

Deploy and customize Palantir Foundry and AIP solutions for enterprise clients. Responsibilities include conducting client workshops, building data pipelines and operational workflows with Python and TypeScript, solving complex technical problems, training end users, documenting solutions, and supporting project delivery. The role requires strong data engineering, communication, analytical, and problem-solving skills, along with recent Palantir experience and approximately 5% travel in Canada and the United States.

Leads the creation of the product organization and enterprise technology strategy for a commercial insurance program administrator. Develops product and AI visions, prioritizes roadmaps, identifies build-versus-buy opportunities, transforms insurance workflows, establishes data and AI governance, and builds high-performing product teams. Partners with executive, underwriting, claims, actuarial, operations, distribution, legal, compliance, engineering, and data leaders to deliver measurable business improvements.

Experienced Data Scientist supporting federal data-driven initiatives through statistical analysis, predictive modeling, machine learning, data preparation, visualization, dashboards, and actionable insights. The role collaborates with technical, business, and program stakeholders, advises on analytical methodologies, improves data quality, and contributes to modernization, automation, and emerging technology efforts.

Drive enterprise SaaS sales across EMEA by prospecting AI and machine learning stakeholders, conducting discovery, presenting Arize’s platform, managing proof-of-concept engagements, navigating complex sales cycles, closing new business, driving adoption, and expanding customer accounts. The role requires full-cycle enterprise sales expertise, strong communication, independent execution, account research, and relationship-building within the AI/ML community.

Develop and improve AI agents and machine learning models that identify financial opportunities in healthcare contracts, supply chain, pharmacy, and managed care data. Analyze complex datasets, automate manual workflows, build information extraction and agentic capabilities, and establish evaluation frameworks. Collaborate with engineering, product, value engineers, and healthcare subject-matter experts to translate research into scalable solutions with measurable financial impact.

Leads development and deployment of statistical, machine learning, and causal inference models for customer decisioning. Designs experiments, estimates treatment effects and incremental value, evaluates targeting performance, and integrates analytical solutions into governed production systems. Partners with business and technology teams, communicates complex findings, and continuously improves models using experimental and operational results.

Lead actuarial pricing for Lemonade’s car insurance products, including state rating plans, rate indications, predictive modeling, pricing strategy, and rate filing support. Partner with Data Science to integrate machine learning models, monitor pricing and underwriting results, assess competitors, and expand into new states. Manage and develop a team of actuaries while supporting scalable pricing tools and data-driven decision-making.

Leads the global Customer Success organization and owns post-sale strategy, retention, expansion, adoption, customer health, and recurring revenue performance. Builds scalable teams, processes, lifecycle frameworks, and operating systems supporting rapid international growth. Integrates AI, predictive analytics, and automation into Customer Success operations while partnering with Sales, Product, Engineering, Marketing, and Operations. Manages executive relationships with strategic customers, drives forecasting accuracy, and ensures measurable customer outcomes across distributed regions.

Lead complex actuarial pricing work for personal lines insurance, including rate indications, regulatory filings, pricing analyses, predictive-model implementation, and state expansion. Develop automation and scalable filing tools, communicate recommendations to technical and executive stakeholders, manage regulatory risks, and coach other actuaries. Partner cross-functionally with Product, Regulatory, Data Science, Engineering, and Finance teams while maintaining analytical rigor and compliance.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Lead product design for Fetch’s Receipt & Rewards experience, connecting receipt capture, account linking, recognition, matching, and rewards. Define design strategy for complex, AI-enabled systems; improve usability, accessibility, trust, and experience quality; and balance user needs, data quality, business goals, and technical constraints. Partner with Product, Engineering, Research, and Data Science, drive cross-functional alignment, shape multi-quarter initiatives, and mentor designers.

Designs, builds, scales, and operates distributed CI/CD services supporting millions of builds, tests, and releases. Develops code for Azure-based infrastructure spanning virtual machines, containers, and custom lab environments. Responsibilities include requirements analysis, architecture and design documentation, estimation, debugging, optimization, operational playbooks, on-call incident response, monitoring, reliability improvements, and mentoring engineers.

Design, develop, and operate scalable software platforms and automation for Azure network qualification infrastructure. Build tools for device provisioning, configuration, lifecycle management, testing, telemetry, and health validation. Develop AI-powered agents for troubleshooting, root-cause analysis, and engineering productivity. Create reliable distributed systems with observability, diagnostics, automated recovery, and scalability while collaborating across software and network engineering teams.

Leads the property insurance product roadmap for Prometheus, owning prioritization across underwriting, accumulation, and portfolio workflows. Builds and manages the Product team, translates carrier needs into precise requirements, validates releases in customer workflows, and drives adoption. Owns insurance model governance, including validation, documentation, change control, and AI-use policies. Requires deep property insurance, catastrophe modeling, geospatial, machine learning, and enterprise product experience.

The Commercial Legal Director will lead complex technology and commercial transactions, negotiate SaaS, licensing, partnership, marketing, and services agreements, and develop scalable legal contracting standards. The role advises teams on AI, intellectual property, privacy, security, and regulatory issues; improves contracting workflows using Ironclad and AI-enabled tools; and partners with senior stakeholders across product, engineering, finance, marketing, and people operations.