Top Machine Learning Jobs in Columbus, OH

Design, build, and scale ML and Generative AI systems. Develop applications using ML architectures and monitor model performance.

As a Software Engineer, AI/ML GenAI, you will design and implement AI features, manage embeddings, and optimize AI systems for production deployment while collaborating with product and design teams.

The Staff Machine Learning Engineer will lead ML initiatives, develop AI systems, optimize pipelines, and mentor team members to automate healthcare processes.

The Applied Scientist AI/ML Intern will work on building data pipelines, finetuning LLMs, and deploying AI models in a collaborative team environment.

Lead the design and operation of Twilio's ML and data platform, architecting cloud-native pipelines and implementing MLOps best practices while mentoring engineers and collaborating across teams.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

Design, implement, and optimize scaled lifecycle campaigns across email and in-product channels to drive activation, revenue, retention, and cross-sell. Use marketing automation, behavioral data, and ML techniques to personalize experiences, analyze performance, and collaborate across growth, product, sales, and data teams.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

The ML Engineer will scale automated evaluation systems for AI models, develop judge models, design validation frameworks, and create synthetic data pipelines.

The Group Product Manager will lead the Real Time Decisioning and 3D Secure authentication product suites, focusing on fraud management and security while enhancing customer experiences. Responsibilities include strategy development, cross-functional collaboration, and product optimization.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

The VP of Engineering will lead a high-performing team to develop AI-enabled technologies, managing technical vision and execution strategies while ensuring product reliability and security in complex environments.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

The Senior Machine Learning Engineer will manage the full ML lifecycle, collaborating with teams to develop scalable systems that improve product decisions and empower monetization strategies.