Top Remote Machine Learning Jobs in Nashville, TN

Lead technical pre-sales for large Oil, Gas & Energy accounts, define and implement Databricks-based data and ML/AI strategies, build technical champions, mentor teammates, and drive enterprise adoption through technical leadership and value selling.

Lead product initiatives for football data analytics and AI experiences: define business cases, understand customer workflows, drive cross-functional squads, own in-product onboarding and customer success, and iterate quickly to deliver measurable outcomes like revenue and retention.

Lead product discovery, prioritize roadmaps, and deliver football data analytics and AI features. Work with design, engineering, analytics, and former NFL experts to build, onboard, and iterate products that drive revenue, retention, and customer success in a fast-paced startup environment.

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.

Lead Felix's global pricing strategy and infrastructure. Define monetization trade-offs, run advanced pricing experiments and elasticity research, partner with Finance on unit economics, and collaborate with Engineering to build automated/ML-driven pricing engines while keeping pricing transparent and user-friendly.

Lead design, build, and operate an end-to-end Identity Platform for KYC/KYB, overseeing CIP, CDD, sanctions screening, and continuous risk monitoring. Drive AI-first automation to reduce manual reviews, mentor engineers, manage reliability and incidents, and represent technical solutions to customers and regulators. Partner cross-functionally to shape roadmap and ensure regulatory compliance and extensibility across jurisdictions.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

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.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

As Co-Founder & CEO, you will define strategy, lead customer development, drive product iterations, raise capital, and build the founding team for InfluTracker, an AI content intelligence venture.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

The Director of Artificial Intelligence will define, lead, and implement AI strategies, managing R&D, building teams, and ensuring ethical AI use to drive business outcomes.

Lead Data Science initiatives, build AI/ML solutions, and mentor teams in a collaborative environment, driving innovation in a leading construction equipment venture.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

The Principal AI/ML Researcher/Engineer will lead research and development of reasoning, planning, and decision-making systems, integrating multi-agent coordination with reinforcement learning to enhance Airbnb's AI capabilities for personalized experiences.

Lead design and delivery of a unified, real-time billing platform that embeds AI/ML to automate reconciliations, detect anomalies, enable predictive insights, and create autonomous finance workflows across global billing operations.

Own end-to-end lifecycle for AI features: define requirements, run model evaluation and experimentation, maintain capability-level AI roadmap, apply responsible AI principles, measure success metrics, iterate with engineering, UX, security, and go-to-market to deliver customer-ready AI capabilities.

Design, build, and maintain scalable AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists and engineers to implement and optimize AI solutions, troubleshoot pipeline issues, document best practices, and develop MVP code to transition into production-ready systems.

Architect and deliver AI-driven documentation systems (TMS/CMS/automation) for regulated technical publications. Design and deploy ML/NLP/Generative AI tools, optimize translation memory, support DITA/XML workflows and FrameMaker templates, build Python scripts for publishing and content reuse, and evaluate documentation workflows to improve localization, quality, and analytics.

Lead and scale engineering teams building Protect, a real-time multi-signal fraud detection platform. Set technical strategy, develop managers and senior engineers, deliver distributed systems and APIs, improve architecture, observability, reliability, and developer productivity while partnering with Product, Research, Security, and exec stakeholders.

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.