Top Machine Learning Jobs in Charlotte, NC

Join Hims & Hers Analytics and Data Science team to engage in data-driven decision making, improve user experience, and contribute to product development. Collaborate with business leaders, marketers, and product teams to drive analytical insights, and leverage machine learning for innovative solutions across the organization.

As a Lead AI ML Engineer, you will design, develop, and deploy machine learning models and data pipelines, drive impactful business decisions, and manage the data infrastructure in collaboration with data engineers and scientists while ensuring high-quality outputs.

As a Tech Lead Manager for Securities Engineering, you will oversee a technical team to develop and manage high-performance trading systems. Your role involves mentoring engineers, developing roadmaps, and ensuring system reliability while collaborating with research and operations teams.

As a Staff Machine Learning Data Scientist, you will lead the development of machine learning tools for patient data, integrating insights from diverse stakeholders, and conducting complex analyses in cloud environments. You'll collaborate with experts to provide innovative solutions and generate novel clinical insights from extensive patient data.

Lead the design and development of robust data architectures that support scalable, secure, and efficient data pipelines. Drive innovation, mentor team members, ensure data quality and resilience, and collaborate with cross-functional teams to deliver impactful data solutions.

As an ML Platform Engineer at Stitch Fix, you'll build and maintain infrastructure for machine learning, develop APIs and platforms, and support data scientists. You'll collaborate with teams to improve systems and foster technical collaboration, enhancing the velocity of innovation within the organization.

As a Staff Machine Learning Engineer at Lily AI, you will design scalable machine learning systems, optimize deep learning models, and implement best practices in ML Ops. You'll collaborate with various teams to define the ML roadmap, improve system performance, and develop tools to enhance team productivity. The role emphasizes automating workflows and transitioning prototypes to production-ready systems.

The Senior Machine Learning Engineer will develop, train, document, and manage machine learning models, collaborating with product teams and the community to enhance Wikipedia and similar projects. Key responsibilities include assessing customer needs, scoping tools, gathering training data, deploying models, and monitoring their performance over time.

As a Senior Machine Learning Engineer, you will develop, train, document, deploy, and manage production machine learning models. You will collaborate with internal and external customers to build scalable models and support other teams in the Foundation while ensuring the effectiveness of machine learning solutions.

As a Senior Machine Learning Engineer at the Wikimedia Foundation, you'll plan, develop, train, document, deploy, and manage production machine learning models. You'll collaborate with internal and external customers to build and maintain scaled models, assess needs, gather training data, and ensure ongoing monitoring and improvement of the models.

The Senior Machine Learning Engineer will develop, train, document, deploy, and manage production machine learning models for the Wikimedia Foundation. The role involves collaboration with internal teams and the broader community to assess needs and implement scalable machine learning solutions, particularly in NLP tasks while working in a remote environment.

The Senior Machine Learning Engineer will plan, develop, train, document, deploy, and manage machine learning models, collaborating with internal and external teams to meet project needs and monitor model performance over time.

The Senior Machine Learning Engineer will develop, deploy, and manage production machine learning models, collaborating with internal and external customers and teams. Responsibilities include training models, monitoring their performance, and providing insights to improve projects like Wikipedia.

Responsible for planning, developing, training, documenting, deploying, and managing production machine learning models, while collaborating with internal and external customers to assess needs and gather training data.

The Principal Engineer - ML/AI will design, develop, and deliver advanced AI and machine learning solutions, translating technical innovations into strategic business outcomes. The role requires leadership in AI, innovative problem-solving, and a comprehensive understanding of emerging technologies to serve the Federal Government clients effectively.

As a Software (ML Product) Engineer at iterative.ai, you will enhance user workflows for DVC, collaborate with technical product managers, and improve MLOps practices within ML teams. Responsibilities include optimizing the tool’s usability and driving projects like dvclive, emphasizing software engineering skills and communication.

As a Senior Software Engineer II for ML Core, you will define architecture and implement changes for backend services. Responsibilities include optimizing search infrastructure, enabling rapid ML model productionalization, mentoring team members, and managing complex projects across teams.