Top Machine Learning Jobs in Columbus, OH

Conduct statistical analysis and exploratory data analysis, write SQL queries, build predictive models, generate forecasts, and communicate findings through data visualization and storytelling. The intern will work on business problems in the insurance industry using R or Python and gain experience across the data science project lifecycle.

Leads the architecture, development, and deployment of scalable AI-driven platforms and software systems. Defines technical strategy, evaluates technologies, establishes AI/ML, MLOps, DevOps, and engineering best practices, and ensures privacy, security, and ethical compliance. Collaborates with business, product, and engineering teams, mentors technical staff, and drives innovation through architecture, testing, CI/CD, and long-term planning.

Supports email and broader marketing analytics through data collection, campaign measurement, reporting, dashboards, statistical analysis, visualization, and optimization recommendations. Partners with marketing teams to translate customer and campaign data into actionable insights. Responsibilities include developing analytical models, conducting qualitative and quantitative research, documenting requirements, supporting implementation, and improving marketing processes and decision-making.

Leads architecture and engineering for consolidating global wide area networks into a unified platform. Defines carrier-scale routing, traffic engineering, resiliency, automation, telemetry, validation, and AI-assisted operational strategies. Oversees transformation plans, migrations, production rollouts, technical standards, risk controls, and reliability improvements while partnering across engineering, infrastructure, cloud, security, operations, and architecture teams.

Leads enterprise data, analytics, cloud modernization, and AI solutions for an actuarial organization. Partners with business and technology stakeholders to define roadmaps, design governed cloud-native data platforms, modernize legacy processes, and deliver AI-enabled capabilities. Oversees architecture reviews, solution design, data governance, security, observability, scalability, and cost optimization while mentoring technical teams and influencing executive technology investments. The role also involves actuarial modeling, valuation, pricing, risk analysis, financial reporting, and reinsurance strategy.

Manage and enhance AML transaction-monitoring models across the full development lifecycle, including data exploration, production deployment, monitoring, tuning, documentation, and validation. Partner with financial-crime teams, model risk management, auditors, regulators, and business stakeholders. Apply statistical and machine-learning techniques to develop anomaly-detection systems, defend methodologies, address validation concerns, and advance the bank’s AML monitoring program.

Owns end-to-end delivery of enterprise AI projects from technical scoping through deployment. Coordinates engineering, data science, and business teams; manages timelines, budgets, resources, risks, and project KPIs. Ensures AI initiatives address regulatory compliance and data privacy requirements, facilitates communication between technical and business stakeholders, and supports successful operational handoffs.

Lead enterprise architecture and digital transformation across business units, developing technology strategies, roadmaps, capability models, governance standards, and architecture guidance for AI, RPA, cloud modernization, and virtual assistant initiatives. Evaluate emerging technologies, lead proofs of concept, and advise senior stakeholders on risks and costs. Qualified candidates should apply with a resume highlighting enterprise architecture, cloud, AI, and RPA leadership experience.

Lead go-to-market strategy for Sprout Social’s AI portfolio, including the Trellis AI agent. Develop enterprise launch playbooks, positioning, executive messaging, campaigns, and enablement programs. Analyze market and competitive dynamics, influence product roadmaps, improve launch processes, and partner with Product, Sales, Revenue, Brand, and executive leadership to drive adoption, revenue growth, deal expansion, and category leadership. The role also mentors marketing team members and operates with substantial autonomy.

Leads technical direction for GitLab’s Core DevOps services, covering CI, CD, planning, and source control. Defines architecture, quality metrics, migration strategies, and technical roadmaps; addresses systemic risk and complex design decisions; prototypes and writes code when needed; partners with Infrastructure, Security, SRE, and Product; adopts AI capabilities; mentors senior engineers; supports incident response and senior technical hiring.

Lead cybersecurity strategy and architecture across products, applications, and technologies. Advise engineering teams, communicate complex risks to leadership, develop reusable security frameworks, create mitigation solutions, and evaluate emerging technologies. The role requires influencing cross-functional teams, shaping enterprise-wide architecture, and applying cloud-native, application, API, web, and mobile security expertise across a complex financial-services environment.

Leads software engineering and AI initiatives for enterprise-scale banking technology. Designs scalable frameworks, writes and reviews production code, and establishes secure, auditable agentic AI development workflows. Defines responsible AI guardrails, target-state architecture, reusable engineering practices, and cloud-native solutions. Advises cross-functional teams, influences senior stakeholders, serves as a technical subject matter expert, and collaborates on product and engineering roadmaps.

Manage a portfolio of advertisers on the Adflow commerce media platform, building relationships, monitoring budgets and campaign performance, presenting business reviews, coordinating onboarding, recommending optimization strategies, and identifying revenue-growth opportunities. The role serves as the primary client contact, collaborates with internal campaign, media operations, creative, and finance teams, and uses performance marketing expertise and analytics to drive advertiser success and long-term partnerships.

Manage a portfolio of advertisers on the Adflow commerce media platform. Responsibilities include client onboarding, campaign coordination, budget and revenue pacing, performance reporting, business reviews, strategic recommendations, optimization feedback, and identifying opportunities to grow advertising spend and channel distribution. The role serves as the primary client contact while collaborating with business development, campaign strategy, creative, media operations, and finance teams.

Leads software engineering for a Machine Learning I/O team, developing secure production code and guiding design, testing, debugging, and operational stability. Drives enterprise adoption and governance of AI-assisted development tools, establishes validation standards for AI outputs, promotes secure and responsible AI practices, and influences technical decisions across teams. Provides technical direction, serves as a subject matter expert, and advocates for scalable cloud-native engineering practices.

Supports product management through customer and market analysis, product metrics reporting, research, and data collection. Partners with product, engineering, data science, governance, and risk teams to define AI use cases, assess data readiness, establish controls, and support accountable AI delivery across the lifecycle.

Lead agile design and development projects for mobile apps and digital products. Coordinate product, design, engineering, marketing, leadership, and client stakeholders; manage project plans, scope, requirements, backlogs, acceptance criteria, deadlines, workflows, and deliverables. Support scoping and client relationship management while ensuring successful end-to-end software launches and alignment with business objectives.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Leads enterprise adoption of AI, machine learning, generative AI, and intelligent automation across federated engineering teams. Defines reference architectures, standards, reusable patterns, and Responsible AI governance while advising delivery teams on secure, resilient, scalable implementations. Influences senior stakeholders, promotes AI-assisted engineering practices, establishes validation standards, and builds communities of practice to improve consistency, delivery speed, and operational readiness.

Develop and operate production ML and AI systems powering patient experiences such as matching, ranking, recommendations, onboarding, and personalization. Build reusable ML infrastructure, pipelines, evaluation, observability, and model-serving capabilities. Provide technical leadership across the ML lifecycle, guide architecture, evaluate custom versus foundation-model approaches, and partner with ML and Patient Engineering teams to deliver reliable, scalable AI products.

Develop and deploy AI/ML models for consumer banking use cases including lead scoring, next-best-action, retention, cross-sell, and customer prioritization. Define success metrics, analyze complex datasets, communicate recommendations to nontechnical stakeholders, and partner with product, technology, governance, risk, and operations teams. Ensure models meet regulatory and model risk standards through documentation, monitoring, drift detection, and retraining.

Develop and deploy advanced AI and machine learning models for branch network optimization, resource allocation, sales effectiveness, and workforce performance. Work with geospatial, demographic, transactional, and behavioral data; collaborate with business, governance, UX, and technology stakeholders; translate model results into business recommendations; and support regulatory model reviews. Apply techniques including spatial and graph-based modeling, reinforcement learning, optimization, and behavioral modeling.

Leads the AI Engineering team across applied AI features and foundational ML infrastructure. Responsibilities include managing Senior and Staff engineers, hiring and coaching, deploying LLM-powered capabilities, building MLOps and AI observability platforms, balancing product delivery with platform investment, and ensuring privacy, compliance, evaluation rigor, and clinical safety in production systems.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.