Top Remote Machine Learning Jobs in Raleigh, NC

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

The role involves developing AI solutions, managing user behavior insights, and deploying large-scale AI services with collaborative efforts in a remote environment.

The Machine Learning Engineer will design, train, and evaluate computer vision models, collaborate on engineering improvements, and deploy ML systems for surgical workflows.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

Lead design and development of AI/ML demos on Snowflake platform, collaborating with product teams to align with releases and providing technical expertise in data science and MLOps.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

The role involves managing data pipelines for 3D generative models, developing infrastructure, collaborating with research teams, and ensuring data quality.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

Lead the design and deployment of scalable ML infrastructure, focusing on MLOps and LLM strategies, while mentoring team members and ensuring operational maturity.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

As a Senior Data Scientist, you will develop models to extract insights from complex datasets, focusing on temporal and geospatial features, while collaborating with engineering teams to implement solutions.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

Develop and deploy machine learning models for predictive analytics, automate risk assessments, and extract data using advanced AI techniques. Collaborate with teams to enhance the product portfolio with innovative solutions.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Staff Software Engineer, you'll develop and maintain backend and pipeline systems for search and recommendation services on Reddit, focusing on low-latency, scalable model-serving APIs.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The AI/ML Engineer will architect, maintain data pipelines, develop AI applications, and optimize distributed systems for fraud detection and prevention.

Implement and optimize production-ready analytics code, maintain Python repositories, research data sources, build predictive models, and collaborate with teams.

This internship focuses on clinical pharmacology and AI/ML modeling, providing experience in developing predictive models using clinical datasets.

Lead product marketing initiatives at Viaduct, creating compelling content, partnering with sales and product teams, and driving demand in the automotive sector.

As a Principal ML Architect, lead technical strategy and client engagements, mentor ML engineers, and oversee project lifecycle in delivering complex AI systems.

As a Junior AI/ML Engineer, you will work on generative AI applications, traditional ML projects, and MLOps, under the mentorship of senior engineers.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

Lead a team of ML Engineers to develop technology for healthcare, emphasizing hiring talent, technical leadership, and collaboration with stakeholders.