Top Artificial Intelligence Machine Learning Engineer Jobs in Las Vegas, NV

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

The role involves preparing traffic data, developing and deploying machine learning models on Google Vertex AI, and collaborating with teams to improve project workflows.

Design, build, and deploy end-to-end production ML systems for audience targeting, lookalike generation, and propensity scoring. Own ML lifecycle from experimentation to production monitoring, leverage distributed/cloud platforms, implement vector similarity and embedding systems, engineer scalable features, and collaborate with engineering and product teams to ensure model quality and operational reliability.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The Data & CVML Manager leads the development of autonomy for vehicles, focusing on data and ML processes from collection to deployment, while managing a team and ensuring technical performance aligned with safety requirements.

The Staff Software Engineer will build and scale machine learning systems for personalization, collaborating with teams to enhance project quality and performance.

As a Fraud ML Engineer, you will ensure authentic human data is processed by building detection systems using adversarial ML techniques and managing backend systems.

As an ML/AI Engineer, you'll build and operate the LLM platform, integrating models, optimizing performance, and collaborating cross-functionally to ensure reliable AI systems.

The AI Software & Data Engineer will design and build full-stack systems, data platforms, and AI prototypes, integrating AI capabilities for enterprise solutions.

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.