Top Remote Machine Learning Jobs in Nashville, TN

Join DICK'S Sporting Goods as a Senior Machine Learning Engineer, focusing on AI-driven search solutions that enhance decision-making and engagement across the organization.

We're looking for an AI/ML Engineer to enhance our edge MLOps solutions, improve ML workflows, and support team development with strong technical expertise in Python and ML frameworks.

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.

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 develop and deploy AI/ML solutions, collaborate with product managers and engineers, and improve learning experiences.

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.

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

Lead the development of AI agents and infrastructure, collaborate with stakeholders, design APIs and SDKs, and advocate for best practices.

The Practice Manager leads Data Science, AI, and ML projects, managing teams, fostering growth, and ensuring customer success through technical guidance and strategic business planning.

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

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

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

The role involves developing AI-driven features for observability tools, collaborating with cross-functional teams, and delivering scalable solutions.

The role involves designing, building, and managing data pipelines and machine learning solutions for veterinary care, utilizing cloud services and various programming languages while collaborating within an Agile team.

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

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 Senior Machine Learning Engineer will lead AI initiatives, develop ML infrastructure, establish data engineering best practices, and collaborate across teams to enhance healthcare technology services.

As a Machine Learning Engineer, you will fine-tune models, shape data pipelines, evaluate AI behavior, and collaborate on product features in a high-autonomy environment.

The role involves fine-tuning machine learning models, designing datasets and pipelines, and ensuring product quality and safety for a new AI application.

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

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

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

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

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

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