Top Machine Learning Jobs in Raleigh, NC

Lead cross-functional Fund Finance projects, manage timelines, communicate with senior leadership, mitigate risks, and mentor junior team members.

The AI/ML Intern will support Cyber AI projects, assist in model design and implementation, create prototypes, and enhance tools, working with a multidisciplinary team.

Seeking a Senior Full Stack .NET Developer to work on a social good project, with strong skills in C#, AngularJS, design, and UX. Requires 5+ years of experience.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

As a Principal Product Designer & Product Manager, you will drive product creation, merging strategy and design while integrating AI tools to enhance workflows. You will lead user research, design processes, and cross-functional collaborations to meet business goals and improve user experiences.

Lead a team to develop Dropbox's AI product, Dash. Focus on driving product revenue, operational agility, and mentoring team members. Utilize ML techniques and data-driven insights for decision making.

Lead the design and delivery of large-scale solutions in Generative AI and Big Data, while mentoring teams and driving innovation.

Lead the data science and machine learning strategy, mentor senior scientists, and drive innovation in Generative AI and Graph ML solutions while aligning with business goals.

Lead the development of cyber forensics and threat intelligence capabilities, build and mentor a team, and create scalable data-driven systems for cyber risk assessments.

The Machine Learning Engineer will develop and enhance ML-powered products focusing on models, metrics, pipelines, and collaboration with product teams.

As a Machine Learning Engineer, you will design systems for safe data ingestion and optimize data usage to enhance models and products, collaborating closely with the Product team and customers.

As a Machine Learning Engineer, you will focus on user-behavioral modeling, collaborate with teams, and engage in data processing and model deployment.

As a Software Engineer at Yobi, you will enhance build systems, deployments, and ML integrations while working within product teams.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

Lead AI engineering initiatives to develop and implement innovative AI/ML solutions while enhancing software development processes across Owlet's products.

The Human Data Operations Manager will design annotation workflows for ML, establish data benchmarks, and partner with cross-functional teams to enhance evaluation processes.

Lead and manage ads analytics efforts at Netflix, focusing on metric standardization, data tool development, and actionable insights delivery.

Lead the ML Understanding team at Reddit, defining technical strategies, overseeing ML pipeline execution, and managing team development while collaborating cross-functionally for AI solutions.

Develop and maintain cutting-edge LLM projects, lead NLP models, own ML systems, and enhance user experiences on Poe platform.

As a Technical Recruiter, you will source and recruit top technical talent for AI/ML and Data Science roles while managing candidate experience and the hiring process.

Develop machine learning driven products and tools for Firefox, lead design and integration of AI models, and mentor junior engineers.

The Senior Staff Machine Learning Engineer will develop AI-powered solutions, mentor engineers, and collaborate with cross-functional teams to enhance Airbnb's customer experience through advanced machine learning technologies.

Lead the product management team and major product lines, focusing on strategy, execution, and cross-functional collaboration to align company goals.

Develop and design learning paths and courses in various technical domains, authoring materials and assessments while collaborating with team members.

Develop and enhance high-volume data pipelines with ML capabilities, while collaborating with engineering teams to integrate data science into products and applications.