Top Remote Machine Learning Jobs in Dayton, OH

The Senior Machine Learning Engineer will design and implement detection systems to improve email security, lead project execution, and mentor junior engineers.

Join TensorOps as a Junior AI/ML Engineer. Work on AI and ML projects, receive mentorship, and contribute to production-grade systems.

Design and build systems for large-scale batch inference workloads, create developer-friendly APIs, and ensure reliability and cost control in ML infrastructure.

Design and implement machine learning bidding algorithms, evaluate their performance with large-scale data, and align them with business goals.

The Staff Firmware Engineer will architect ML infrastructure for edge devices, integrating new sensors and mentoring the firmware team to advance on-device ML solutions.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

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

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 Engineering Manager - Data & ML will redesign and scale Underdog's data and ML platform, establishing best practices, leading a team, and collaborating with cross-functional teams to optimize data systems.

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

As a Sr. AI/ML Engineer III, you will design and implement reinforcement learning algorithms, integrate them into simulation environments, and evaluate their performance. Collaborating with engineering teams, you will ensure the maintainability and transparency of AI components while communicating results and recommendations clearly.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

The ML Platform Engineer will develop and scale ML infrastructure, automate workflows, and collaborate with data scientists to deploy models efficiently in production.

The role focuses on enhancing detection frameworks using machine learning to identify malicious activities and minimize risks for Netflix.

Develop and optimize machine learning models for financial and operational workflows at Netflix, ensuring model reliability and integration with studio applications.

Build and deploy ML systems that detect fraud and automate security decisions, while collaborating with cross-functional teams.

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 Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

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

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

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 Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.