Top Machine Learning Jobs in Dayton, OH

Lead development of a large-scale machine learning platform, optimizing model training, data processing, and collaborating on MLOps, while ensuring scalability and performance.

Lead development of data pipelines and workflows for ML models, design scalable data processing environments, and ensure high data quality.

As a Machine Learning Engineer, you will develop online prediction systems and offline recommendation engines to optimize e-commerce profitability by leveraging machine learning models and data-driven insights.

The Senior Full Stack Engineer will develop AI/ML features for ClickHouse Cloud, integrating AI capabilities and building user-friendly interfaces.

As a Senior Python Engineer at ClickHouse, you will enhance the Python ecosystem for data scientists and ML teams, ensuring efficient data integration and optimizing workflows within the open-source environment.

As a Senior Machine Learning Engineer, you'll design and build AI systems, manage ML lifecycles, and create recommendation and retrieval systems while collaborating cross-functionally.

Design and build infrastructure for ML model training and deployment. Collaborate with teams and monitor performance using AWS tools. Focus on reliability and efficiency in high-availability environments.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

The role involves developing machine learning models for Netflix's Studio, collaborating with teams, and scaling ML solutions for data analytics.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

The role involves designing scalable AI solutions, managing large-scale AI deployments, building client relationships, and delivering presentations. Requires experience in MLOps and knowledge of ML ecosystems.

The Machine Learning Engineer will enhance search retrieval, train ranking models, build query understanding systems, and ensure robust pipelines for Reddit's AI-driven products.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

As a Research Intern, you will work on AI/ML projects, contributing to the development of the Nebula LLM and applying machine learning techniques to real-world problems.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

As a Software Engineer, you'll enhance the user experience of ML tools, optimize workflows, and collaborate with product managers on ML infrastructure projects.

As a Machine Learning Engineer, you will develop and deploy AI/ML solutions, collaborate with product managers and engineers, and improve learning experiences.

The Senior Software Engineer will develop and maintain foundational ML infrastructure for feature computing, storage, and retrieval, impacting numerous teams at Reddit.

Develop ML models and pipelines for autonomous tractor initiative, improving system safety and performance in production environments.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

Develop and optimize large-scale ML models and training pipelines for automating PCB layouts, collaborating on data pipeline design and novel architectures.

As a Senior ML Ops Engineer, you'll build ML infrastructure, implement automated deployment, optimize model serving, and ensure production performance.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.