Top Machine Learning Jobs in Columbus, OH

Embed with strategic higher-education partners to design, build, and ship production AI and platform integrations (LLM/RAG, LTI) across Cengage products. Own end-to-end deployments, write production code, ensure compliance and accessibility, evaluate AI safety and outcomes, mentor FDEs, and translate field learnings into product roadmap contributions.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Integrate LLMs, RAG, and agentic-AI into secure decision-support software. Design prompts and inference workflows, connect AI to backend services, evaluate outputs, build tests, document designs, and collaborate with engineering, security, and DevSecOps teams to deliver reliable mission-capable AI features.

Design, build, and deploy machine learning models for a payments platform, overseeing end-to-end solutions and experimentation, while monitoring models in production.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

Lead software development initiatives for a global SaaS platform: design, develop, and test complex front- and back-end systems. Drive architecture, code quality, and mentorship; oversee multiple projects and teams. Solve scalability, metadata, search, and asset-processing challenges; collaborate with product and leadership to define roadmaps and integrate AI into the development process.

Lead technical execution across backend, frontend, mobile, AI, and data. Translate ambiguous product goals into technical plans, unblock hard engineering problems, coordinate cross-domain work, raise engineering quality, define hiring needs and technical evaluation standards, and build internal AI workflows to foster an AI-native engineering culture.

Lead technical pre-sales and enterprise rollouts by owning infrastructure strategy, PoCs, migrations (on‑prem to cloud), DMS/CRM integrations, InfoSec discussions, and stakeholder engagement with C-level sponsors to enable scalable deployments and upsell opportunities.

Lead development and delivery of AI-enabled discovery experiences for FirstSearch. Define product strategy, roadmaps, and pricing; translate researcher needs into semantic search and NLU features; partner with engineering, design, marketing, finance, and user groups to launch and iterate products; oversee cross-functional workgroups, market analysis, and go-to-market activities to drive value for member libraries.

Design, develop, and test complex software systems; lead small teams and mentor junior engineers; participate in architecture, conduct code reviews, and ensure high-quality delivery with cloud and AI integrations.

Lead and grow OCLC Research Library Partnership metadata community by convening metadata experts, designing programs and working groups, advising partners on metadata strategy and migration, advocating OCLC positions externally, and informing product and research priorities through thought leadership and community-driven initiatives.

Lead and manage high-volume library technology implementations from initiation through completion. Conduct virtual and onsite workflow analysis, configure service options, manage data migrations, coordinate cross-functional teams, track project status, report satisfaction metrics, and deliver consultative services to ensure successful adoption of OCLC products and integrations.

SoftSnow is seeking an AI Ethicist to define ethical guidelines, assess risks, and ensure compliance in AI implementations across various industries.

Design and implement NLP and LLM-powered pipelines to extract, summarize, and semantically search technical documentation. Fine-tune transformer models, build RAG systems, convert unstructured documents into structured knowledge, optimize inference for production, and collaborate with engineers and SMEs to deploy document intelligence solutions.

Lead program delivery for engineering teams at Arine, optimizing internal processes and ensuring timely execution of technical programs while facilitating Agile methodologies.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.