Top Machine Learning Jobs in Memphis, TN

Lead and manage a team of engineers in developing Affirm's Fraud Decisioning System, focusing on innovation and cross-functional collaboration with various stakeholders.

Lead technical vision and execution for enterprise-scale AI, automation, and data initiatives. Architect scalable, secure AI systems and data pipelines, mentor engineers, drive cross-functional alignment, and deliver high-impact production solutions that improve productivity and business outcomes.

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

As a Senior Software Engineer, you'll enhance servicing decisions with ML models, improve experimentation, and scale decisioning systems for personalized borrower experiences.

Lead the design and implementation of ML training systems, manage a team, promote engineering culture, and drive product development.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

Research Scientist at Upstart will develop machine learning models to enhance borrower risk predictions, design prototypes, and collaborate with cross-functional teams while mentoring junior members.

The Engineering Manager will lead a team in developing a Dispatch Optimization platform, focusing on data science, ML engineering, and operational efficiency, while fostering talent and ensuring project delivery.

Lead the architectural vision and engineering for IAM and workforce security at Coinbase, integrating security with business goals across complex cloud ecosystems and SaaS applications while mentoring teams and influencing risk strategies.

Lead the AI Platform team at Zapier, focusing on enabling product teams to ship AI/ML-powered features efficiently and safely.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Principal Product Manager, AI will lead the AI platform strategy at Webflow, collaborating across teams to enhance product innovation and growth, and develop a unified AI strategy based on customer insights.

As an AI Integrations Staff Engineer at Vetcove, you'll integrate AI models like ChatGPT into existing products, optimize performance, and collaborate with data science teams to enhance user experience.

Own and scale Coinbase's notification platform and experience to grow MAU, drive engagement, and maximize LTV using ML-driven personalization, analytics, and cross-functional execution.

Design and implement the core Risk platform architecture, manage projects, mentor team members, and write high quality code for Coinbase products.

The AI Engagement Manager will foster relationships with top partners, facilitate adoption of AI solutions, and analyze performance using BI tools.

Lead the product vision, strategy, and execution for Consumer Risk within Checkout at Affirm, focusing on credit decisioning, pricing, and fraud prevention while managing a team of Product Managers and collaborating with various functional teams.

As Principal Product Manager for the Agentic Platform, you will set the vision and strategy for AI infrastructure, drive product development, and facilitate adoption across teams.

Lead research on large language models to address healthcare challenges, collaborating with teams to enhance model performance and ensure real-world applicability.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.