Top Machine Learning Jobs in Raleigh, NC

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

As a Data Science Intern, you'll analyze data to derive insights, develop solutions, and assist teams with data-driven workflows and reporting.

As Growth Marketing Lead, you'll drive scalable customer acquisition through optimizing paid marketing channels, beginning with Google, and potentially transition into leadership as strategies scale.

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

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

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 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.

Lead an R&D ML team to develop and deploy AI/ML solutions for semiconductor manufacturing. Guide cross-functional research, mentor engineers in computer vision, physics-informed ML, and reinforcement learning, and apply materials science expertise to advance product development.

Senior leader responsible for designing and operating Fidelity's global sanctions program, ensuring OFAC and parallel-regime compliance, driving strategy, governance, technology-enabled screening and analytics, regulatory engagement, and leading a global sanctions team to mitigate enterprise sanctions risk.

The Senior Director of Marketing Technology leads the marketing technology and data strategy, focusing on AI, integration, and analytics for enhanced customer engagement.

Lead AI advisory practice by managing client relationships, driving growth, developing strategies for implementation, and ensuring successful delivery outcomes while mentoring team members.

Design, build, and maintain scalable ML systems, focusing on production infrastructure and empowering data scientists through AI tooling and collaboration.

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.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Design, develop, and review complex backend systems; translate product requirements into software designs; debug and resolve technical issues; mentor junior engineers; implement CI/CD, containerization, and model training/serving; collaborate with stakeholders and maintain best practices.

Lead strategy and implementation of AI-assisted caselaw content collection, conversion, enhancement, and global deployment; define standards, guide model development, measure performance, and drive cross-functional adoption.

Seeking a Distinguished Technologist to lead AI architecture and design for HPE's Private Cloud AI offerings, focusing on applied AI, agentic AI, and generative AI. Responsibilities include technical leadership, implementation, and mentoring engineers while optimizing AI systems for cloud-based solutions.

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

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.