Top Machine Learning Jobs in Cleveland, OH

Own analytics for Root’s Customer Experience domain and policyholder retention. Develop metrics, analytical frameworks, experimentation systems, and strategic recommendations. Partner cross-functionally with Product, Engineering, Data Science, and Operations to shape roadmaps, evaluate customer initiatives, quantify business impact, and influence senior leadership decisions through rigorous analysis and clear communication.

Build and scale Pulse’s technology partner ecosystem by recruiting and signing partners, structuring integrations and commercial agreements, developing joint go-to-market and co-sell programs, and driving partner-sourced pipeline, revenue, and API usage. The role also manages partner onboarding, enablement, deal attribution, forecasting, technical validation, and feedback to product and engineering teams.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Own the strategy, roadmap, and delivery of AI-powered capabilities across Mapbox Maps. Partner with engineering, customers, and cross-functional teams to identify use cases, prioritize development, validate solutions, and launch products. Manage pricing and packaging, sales enablement, marketing, trials, and partnerships while driving customer adoption, business growth, and scalable experiences for developers and end users.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Own the platform powering Airbnb’s AI Assistant, including request routing, knowledge retrieval, capabilities, actions, and evaluation. Set product strategy, define resolution and quality standards, analyze production data, diagnose system failures, and guide engineering, data science, policy, and knowledge partners. Lead generative AI launches, safety and readiness reviews, LLM evaluation systems, calibration, and certification while aligning cross-functional teams and communicating decisions to executives.

Owns the intelligence platform roadmap for enterprise healthcare engagement, including decisioning, orchestration, integrations, interoperability, identity and consent management, and scalable deployment. The role defines strategy and requirements, prioritizes platform investments, leads partner integrations, establishes success metrics, and coordinates Engineering, AI/ML, Data Science, Security, Design, and client teams. It also embeds healthcare compliance, security, and responsible AI throughout the product lifecycle.

Own the enterprise AI strategy, roadmap, governance, investment priorities, and measurement framework. Identify and prototype high-value AI use cases, guide pilots into production, establish responsible-AI standards for sensitive data, and communicate outcomes to executives. Build adoption through enablement and reusable practices while coordinating technology, business, legal, security, data, and vendor partners. Lead the emerging AI strategy function and hold teams accountable for delivery and value realization.

Advise Product, Engineering, Security, and business teams on software, SaaS, cloud, privacy, cybersecurity, AI, intellectual property, and emerging technology regulations. Guide products throughout their lifecycle, assess legal and regulatory risks, draft agreements and privacy documentation, support privacy-by-design, monitor global regulations, and develop scalable legal processes, playbooks, policies, and training.

Develop and deploy statistical and machine learning models for credit risk, delinquency, defaults, loan losses, underwriting, and risk-based pricing. Analyze credit bureau, alternative, and loan performance data; build production-ready analytical pipelines; monitor model performance; and address data anomalies. Lead complex initiatives, mentor colleagues, document methodologies, and incorporate model governance, fair lending, privacy, and responsible AI considerations while partnering with Credit Risk, Product, Engineering, and Finance.

Drive AI-enabled product strategy and execution by identifying customer opportunities, defining requirements, and partnering with engineering, design, data, sales, marketing, and customers. Lead development of products using LLMs, generative AI, RAG, and intelligent agents; validate roadmap priorities, communicate product vision, support launches, and improve feature adoption. Apply AI tools to accelerate product specifications, workflows, and software delivery.

Leads revenue, go-to-market execution, forecasting, and organizational growth for strategic enterprise accounts. Builds and manages sales leadership and enterprise account teams, drives AI-focused value selling, oversees complex negotiations, and develops Fortune 500 and Global 2000 relationships. The role partners cross-functionally on customer expansion, product strategy, marketing, customer success, hiring, budgeting, and operational planning. Requires extensive enterprise SaaS sales leadership, experience with developer tools or cloud infrastructure, AI solution expertise, and executive-level engagement.

Implements and maintains cloud security controls across Microsoft 365 GCC High, Azure, AWS, and hybrid environments. Administers cloud security platforms, integrates telemetry, supports vulnerability remediation, and validates controls against CMMC, NIST, DFARS, ITAR, ISO 27001, and other requirements. Secures generative AI, machine-learning, copilot, RAG, and agentic systems through access controls, sandboxing, logging, and execution safeguards. Performs risk assessments, control testing, audit evidence collection, SOC escalation support, automation, documentation, and occasional off-hours incident support.

Designs, implements, and maintains cloud security controls across Microsoft 365, GCC High, Azure, AWS, and hybrid environments. Leads cloud and AI security architecture, threat modeling, infrastructure-as-code automation, security testing, posture management, and incident support. Develops secure patterns for generative AI, machine learning, copilots, agents, and CUI workloads. Translates CMMC, NIST, DFARS, ITAR, ISO 27001, GDPR, and related requirements into technical controls, evidence, and risk mitigations while mentoring engineers and guiding cross-functional teams.

Leads enterprise healthcare interoperability strategy, operations, connectivity, and strategic partnerships. Establishes operating models, roadmaps, KPIs, governance, and partner ecosystems across EHRs, HIEs, QHINs, payers, providers, and data networks. Translates regulatory and technical requirements into scalable capabilities, supports product and commercial growth, oversees investments and agreements, and builds high-performing teams. Requires executive leadership in healthcare data exchange, interoperability standards, regulatory strategy, operations, partnerships, and technology commercialization.

Designs end-to-end architectures and high-level designs for web security products and features, spanning configuration, reporting, runtime systems, analytics, and attack detection. Collaborates with product management and cross-functional teams to define requirements, guides engineering implementation, presents designs, and contributes security product expertise and technical roadmap direction.

Leads strategy, roadmap, development, and lifecycle management for IoT- and AI-enabled manufacturing products. Partners with engineering, R&D, data science, marketing, sales, customers, and global stakeholders to integrate sensors, actuators, cloud platforms, machine learning, and computer vision. Drives predictive maintenance, quality automation, process optimization, security compliance, market analysis, and customer-centric product improvements.

Manage a portfolio of Risk Engagement Strategy and AI Strategy initiatives, including learning programs, leadership visits, communications, automation, and AI use-case delivery. Build project plans, coordinate cross-functional stakeholders, track risks and dependencies, manage governance, support UAT and implementation readiness, and create executive reporting and Tableau dashboards covering milestones, adoption, and value realization.

Develop technical AI and data solutions for aerospace engineering applications. Responsibilities include designing architectures, building proof-of-concepts, coding and debugging applications, developing machine learning systems, presenting solutions to stakeholders, and shipping cloud-based products to production. The intern will gain experience with data engineering, cloud platforms, databases, web design, AI technologies, and numerical methods while collaborating across teams.

Develop and demonstrate AI and data solutions for aerospace engineering projects. Responsibilities include designing architectures, building proof-of-concepts and machine learning systems, writing code, creating demos, supporting cloud and data engineering initiatives, and delivering production-ready solutions. The intern will collaborate cross-functionally, participate in design thinking, gain mentorship, and work on real-world projects using technologies such as Python, cloud platforms, machine learning, LLMs, and computer vision.

Leads customer engagements and large-scale analytics projects from inception through delivery, ensuring measurable business value, quality, budgets, and timelines. Builds customer relationships, translates needs into analytics solutions, supports renewals and expansions, and coordinates with product, engineering, and data science teams. Also supports solution architecture, pre-sales demonstrations, proof-of-concept implementations, technical use-case development, and customer conferences. Presents complex insights to technical and nontechnical stakeholders.

Lead CluePoints’ alliance and channel strategy across technology partners, systems integrators, consultancies, and regional resellers. Build partner-sourced revenue, develop channel programs, enable partners, manage complex commercial relationships, and collaborate with Sales, Marketing, Product, and Services. The role will establish partnerships in markets including Japan, India, and Europe, while eventually building and leading a partnerships team.

Leads portfolio planning and cross-functional execution for Data Science Core and GenAI Studio programs. Establishes roadmaps, operating rhythms, priorities, dependencies, risk management, readiness criteria, decision processes, and success measures. Coordinates data science, engineering, product, research, privacy, legal, security, and business stakeholders from problem framing through deployment, adoption, and monitoring. Communicates technical tradeoffs and responsible AI considerations while improving team effectiveness, capacity planning, documentation, and delivery practices.

Create, solve, review, and validate coding-heavy machine learning tasks for AI training. Build and optimize models, training and inference workflows, data pipelines, evaluation systems, and reproducible Python workflows. Diagnose numerical and system-level failures, improve memory use and throughput, and verify technical correctness while working with coding agents.

Leads quantitative and qualitative market research on international development, AI adoption, institutional demand, funding, procurement, competition, and commercial opportunities. Evaluates AI and data service applications, develops market assessments and strategic recommendations, manages research initiatives, prepares executive presentations, and collaborates with leadership, technical, operational, and business development teams to support market entry and growth.