Top Machine Learning Jobs in Columbus, OH

Lead end-to-end ML system development: data exploration, model research, training, deployment, evaluation, and MLOps. Collaborate cross-functionally to prioritize claims, improve matching, measure business impact, and own a technical workstream.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Develop, validate, and improve machine learning models (regression, classification, forecasting, optimization). Prepare data, perform feature engineering, train and evaluate models, and support deployment with Data/ML Engineering. Communicate results, document methods, and collaborate on experiments and cross-functional initiatives.

Build and maintain Quora's ML platform and ranking infrastructure to serve large-scale ML models. Work on GPU model serving, distributed systems, developer tooling, feature store modernization, and on-call rotation to ensure high availability, performance, and cost efficiency.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

Lead end-to-end development of fraud and risk ML systems: define problems, engineer features, build and evaluate models, collaborate with product and engineering, deploy with ML engineers, and monitor production performance to detect drift and trigger retraining.

Lead AI/ML consulting engagements: design and implement ETL, data modeling, predictive models, anomaly detection, distributed data pipelines, and executive-ready visualizations. Drive business development, mentor teams, and deliver client-facing solutions in hybrid/onsite environments.

Lead AI/ML consulting engagements, build and deploy machine learning models and ETL pipelines, analyze large datasets, design data architectures, deliver visualizations, drive business development, and manage client-facing teams in high-stakes situations.

Design, build, evaluate, and deploy predictive ML models across regression, classification, NLP, computer vision, and time-series problems. Perform data cleaning, feature engineering, EDA, model selection, tuning, explanation (SHAP, feature importance), and collaborate with engineers and stakeholders to operationalize and monitor models in production.

As a Staff Data Scientist, you will lead initiatives to build and optimize machine learning models, collaborate across departments, and solve complex business problems using data.

The Staff Engineer will design and manage ML infrastructure while mentoring teams, driving MLOps strategies, and ensuring compliance in healthcare data systems.

Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

Design and develop machine learning systems for construction robots, including scalable infrastructure, computer vision models, and data analysis for performance improvement.

Build and design backend services, AI agents, and machine learning models. Collaborate cross-functionally to deliver AI features and maintain code quality.

As a Senior Machine Learning Engineer at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

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.