Top Machine Learning Jobs in Columbus, OH

The Strategic MSP/MSSP Account Executive will identify and develop partnerships, create strategic plans, and drive revenue growth by engaging with prospective MSP/MSSP partners while collaborating internally to optimize sales strategies and maintain relationships.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

Lead client-facing analytics projects to analyze large datasets, design predictive models and reports, deliver actionable insights, and mentor junior analysts. Build statistical and ML solutions (including NLP), automate processes, create dashboards and visualizations, engage stakeholders to define metrics, and present findings to senior leadership to improve cost, efficiency, and quality.

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.

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

The role manages design and implementation of AI solutions, collaborates with data science teams, ensures compliance, and leads AI Ops team.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

Provide legal support for commercial transactions, IT/SaaS agreements, licensing and procurement. Review, negotiate contracts, advise senior management on legal risks, and support compliance across the organization.

Serve as a strategic OD and talent partner advising leaders, designing and delivering organization design, change management, leadership development, succession planning, and talent programs. Leverage assessments, HR systems and data to measure impact, lead enterprise initiatives, partner with HR and external vendors, and scale OD solutions globally.

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 strategy, roadmaps, and execution for OCLC's resource sharing products to improve fulfillment, automation, and delivery. Manage a product team, partner with development, finance, and marketing, drive revenue and profitability, run market analysis, customer workshops, and produce product/business plans, go-to-market materials, and metrics.

Design, implement, and operate key components of a high-throughput link harvesting and evaluation pipeline. Lead architecture and technical decisions, mentor junior engineers, adopt AI/ML (LLMs) in production, ensure system reliability and low impact on other services, and maintain high code quality with CI/CD and production support.

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.

Lead and grow the SHARES resource sharing network and RLP program by setting strategic priorities, running outcome-oriented working groups and town halls, translating community insight into product and policy recommendations, managing partner engagement, and partnering with internal product, support, and research teams to pilot and operationalize next-generation resource sharing (including AI-enabled smart fulfillment).

Learn and contribute to software development by writing, debugging, and testing code under senior guidance. Assist in development and maintenance, perform unit tests and code reviews, troubleshoot issues, and collaborate with product, design, and engineering teams to implement features.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

Build and operate ML training and serving infrastructure by designing, developing, and launching backend systems. Collaborate across teams to decompose projects, support operations and on-call, create monitoring and metrics, perform code reviews, and contribute to developer velocity and platform reliability.