Top Senior Machine Learning Jobs in Columbus, OH

Develop and maintain pricing and predictive models for credit insurance products. Analyze claims, loss ratios, portfolio performance, profitability, credit risk, and economic scenarios. Recommend pricing actions, support forecasting and reserves, evaluate underwriting strategies, and partner with underwriting, finance, claims, data science, and technology teams. Ensure model governance, documentation, and actuarial standards compliance.

Owns the strategy, roadmap, requirements, backlog, positioning, and lifecycle execution for proprietary software products. Partners with engineering, UX, QA, architecture, data operations, and project management teams in an Agile environment. Conducts market and competitive analysis, supports product launches, creates AI prototypes, develops client-facing content, and contributes to RFP responses. Requires strong technical, product leadership, communication, prioritization, and stakeholder-management skills.

Build rigorous ROI analyses, value models, and business cases that translate AI ranking performance into revenue, margin, and cost-to-serve outcomes. Present analyses to CFOs, procurement teams, and other economic buyers; support sales pursuits; create reusable value-selling frameworks; tailor models to customer economics; and collaborate with product, data science, and customer teams to validate benchmarks and deployment results.

Own the full Global System Integrator partner lifecycle, including sourcing, agreements, joint go-to-market motions, enablement, delivery planning, and performance optimization. Build relationships across major GSIs such as Accenture, Deloitte, Bain, BCG, Slalom, and IBM. Collaborate with sales, product, and engineering teams to generate partner-sourced and influenced pipeline and revenue. Develop the GSI strategy, playbook, and operating processes for Sequen’s growing AI business.

Build and operate production machine learning systems for Airbnb Payments, including LLM agents, real-time fraud detection, anomaly detection, personalization, and checkout optimization. Design, train, deploy, monitor, and continuously improve batch and streaming AI applications at global scale. Partner with product, engineering, operations, and data science teams, establish model governance and testing standards, and mentor engineers.

Drive go-to-market reporting, business intelligence, forecasting, dashboard development, and ad hoc analysis. The role standardizes forecasting processes, maintains analytical documentation, automates reporting and data pipelines using AI-assisted tools, and delivers actionable insights to Sales, Marketing, Engineering, Finance, and executive stakeholders.

Build and lead the organization-wide adoption of generative AI, agentic systems, and AI-assisted development. Design production automation agents, evaluate coding tools, modernize rules-based workflows with ML, and establish responsible AI guardrails. Partner with engineering, product, data, and clinical teams to identify high-impact opportunities, own the enablement roadmap, measure outcomes, and drive adoption through working software, documentation, and hands-on collaboration.

Leads business analysis for AI and automation initiatives, identifying adoption opportunities, developing business cases, gathering requirements, and aligning business needs with technical solutions. The role facilitates stakeholder workshops, supports solution design, testing, deployment, change management, governance, and benefits realization. It also advises executives, monitors outcomes, promotes business analysis standards, and mentors junior analysts.

Leads operational oversight, performance analysis, governance, and continuous improvement for AI-powered products and services. Develops performance frameworks, executive dashboards, business insights, risk and compliance reporting, and scalable AI operating models. Partners with AI engineers, product teams, and business leaders to optimize workflows, support automation, manage operational risks, and drive cross-functional operational excellence.

Leads the strategy, roadmap, development, launch, and optimization of AI-powered products. Defines product vision, requirements, priorities, success metrics, and adoption goals while coordinating engineering, AI, business, executive, and customer stakeholders. Evaluates emerging AI capabilities, supports responsible AI governance, manages product performance, and drives continuous improvement aligned with business objectives.

Leads analytical and scientific strategy for Fetch’s Play and Rewarded Apps businesses. Develops predictive and machine learning models, experimentation frameworks, causal analyses, feature pipelines, and measurement systems using Python and SQL. Partners with Product, Marketing, Engineering, and business leaders to improve monetization, engagement, retention, personalization, and marketplace outcomes. Translates complex findings into strategic recommendations, mentors data scientists and analysts, and establishes analytical best practices.

Own the full machine learning lifecycle for search ranking and retrieval, including model training, deployment, serving, feature pipelines, evaluation frameworks, hybrid lexical-vector retrieval, large-scale embedding inference, query understanding, and permissions-aware multi-tenant search. Collaborate with infrastructure, AI, and backend teams to improve search relevance across ClickUp’s platform.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy; delivers executive dashboards, KPI scorecards, operational reporting, semantic models, and self-service BI. Establishes data governance and metric standards, ensures data quality, partners with Engineering, Product, Finance, Operations, and executives, and translates business questions into actionable analytical solutions. Mentors analytics talent and drives prioritization, adoption, and measurable business outcomes.

Senior backend engineer responsible for setting technical direction, designing scalable distributed systems, building customer-facing web applications, mentoring engineers, and applying machine learning to large-scale healthcare data. The role requires Java, Scala, or Rust expertise, cloud systems experience, technical design leadership, cross-functional collaboration, and adoption of agentic engineering practices.

Build and operate production retrieval-augmented generation systems, including embeddings, vector retrieval, grounded language-model generation, citation validation, prompt and schema design, model packaging, serving, rollback, and telemetry. Develop bounded model assistance for narrative extraction with provenance and rule-context tracking. Maintain resilient serving paths in secure government cloud environments, including restricted or air-gapped deployments.

Own the architecture and hands-on implementation of production MLOps systems, scalable inference services, model deployment pipelines, monitoring, and governance. Integrate machine learning into pharmaceutical manufacturing, process control, automation, and scientific or clinical applications. Collaborate with chemical engineers, computational biologists, and platform teams while establishing enterprise CI/CD and MLOps standards. This is a hands-on senior role requiring hybrid onsite work in Indianapolis.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Own the full enterprise sales cycle for Oversee’s leisure travel business, from prospecting through closing. Build relationships with OTAs, agencies, tour operators, and vacation providers; develop pipeline; identify target segments and use cases; refine positioning and sales strategy; lead complex stakeholder processes; and partner with Product and Engineering to convert market insights into a repeatable leisure sales motion.

Own AgentSee’s sales and go-to-market strategy as the first dedicated sales leader. Personally close early enterprise opportunities, refine the ideal customer profile, positioning, pricing, packaging, and sales process, and translate AI capabilities into measurable business value. Build repeatable sales operations and playbooks, provide market feedback to Product and Engineering, and eventually hire and lead the AgentSee sales organization.

Leads the design, development, deployment, and operation of scalable machine learning solutions and high-performance microservices. Builds real-time inference systems using Triton and TensorRT, guides distributed cloud architectures, participates hands-on in coding and reviews, and mentors engineers. Drives technical strategy, operational excellence, system resilience, and business-wide innovation across generative AI, graph machine learning, and big data initiatives.

Lead exploration and application of large language models and generative AI for enterprise contact-center automation. Translate research into high-performing, deployable ML systems; contribute across experimentation, implementation, and deployment; collaborate with engineering and product teams; optimize performance; and help shape team strategy, innovation, and professional growth.

Lead exploration and application of large language models and generative AI, translate research into deployable ML systems, and guide strategic direction. Develop solutions across experimentation, implementation, and deployment while collaborating with engineering and product teams to optimize performance and customer outcomes in contact center automation.

Lead production-grade ML systems: build data pipelines, training and evaluation workflows, and scalable GPU inference. Fine-tune and adapt large models (LoRA, QLoRA, SFT, DPO, distillation), optimize deployments for latency/cost/reliability, and collaborate with product and engineering to ship robust, observable model-driven features.

Lead the end-to-end ML execution: build and operate data pipelines, training and evaluation systems, and scalable inference. Fine-tune and optimize large models (LoRA/QLoRA/SFT/DPO/distillation), ensure GPU efficiency, monitor production quality, collaborate with product and application engineering, and rapidly ship reliable, safe ML solutions that translate research into production.

Manage post-sales relationships with a portfolio of customers, primarily financial institutions, to drive adoption and business outcomes from BioCatch’s behavioral biometric solution. Responsibilities include strategic consulting, project coordination, risk and escalation management, customer presentations, quarterly business reviews, roadmap feedback, stakeholder communication, team coaching, statements of work, and identifying expansion opportunities with account managers.