Top Machine Learning Jobs in Las Vegas, NV

The Senior Software Engineer will design and maintain ML infrastructures using Kubernetes, optimize ML inference with CUDA, and enhance CI/CD processes. The role involves leading model scheduling and resource allocation efforts while collaborating with teams to innovate ML deployment systems.

The Senior Software Engineer will collaborate with experts to build scalable machine learning solutions for autonomous systems, focusing on data management and workflow orchestration. Responsibilities include designing and implementing cloud services and optimizing training pipelines.

The Staff Machine Learning Engineer will develop and fine-tune machine learning models, apply statistical techniques to analyze unstructured data, utilize pre-trained language models, optimize models for production, monitor performance, and work with teams to enhance product features and solutions.

As a Staff Machine Learning Engineer at Fakespot, you will apply machine learning techniques to analyze unstructured data, develop and fine-tune models for text-related tasks, optimize models for production, monitor performance, and collaborate with cross-functional teams to enhance features and solutions.

As an MLOps Specialist, you will design and implement data systems and architectures to enhance data science processes. Collaborate with data scientists to improve modeling pipelines, build infrastructure, and handle data transformation. This role involves deploying models in production environments, utilizing cloud services like AWS, and supporting a team-oriented culture.

As an AI / ML Developer at DuploCloud, you will design and optimize machine learning models, work with large datasets, deploy models in production, develop APIs, and collaborate with cross-functional teams to create AI solutions, ensuring performance and scalability.

As a Senior Machine Learning Engineer, you will design and engineer ML systems for various industries, promote technical thought leadership within the data science team, and work across different ML approaches. Responsibilities include collaborating with stakeholders, addressing technical challenges, and deploying production ML solutions in a cloud environment.

The Lead MLOps Engineer will design and implement scalable MLOps pipelines for deploying and monitoring ML models to optimize the model lifecycle, collaborating with cross-functional teams for data ingestion, model development, and deployment, making a significant impact on advanced analytics capabilities.