Top Remote Machine Learning Jobs in Las Vegas, NV

Design, develop, and deploy production ML models and scalable pipelines. Collaborate with cross-functional teams, optimize model performance, implement MLOps deployments, monitor model health, and document experiments and metrics.

The Staff GenAI Backend Engineer leads engineering for intelligent routing systems, collaborates with teams to enhance customer support, and maintains architectural integrity in a high-availability environment.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

The Principal Machine Learning Engineer will fine-tune and optimize LLMs for various applications, develop AI products, and enhance ML infrastructure in collaboration with cross-functional teams.

The role involves developing and optimizing machine learning systems for voice experiences, focusing on speech recognition and language understanding. Responsibilities include training models, ensuring performance metrics, and collaborating with cross-functional teams for successful deployment.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The Principal AI Platform Engineer will design and maintain the infrastructure for AI systems, ensuring integration, security, and scalability for GenAI products.

The Lead Machine Learning Engineer will design and evaluate models for autonomous driving systems, mentor junior engineers, and utilize large datasets to improve ML capabilities at May Mobility.

The Engineering Manager will oversee a team managing cloud data engineering projects, client engagement, and technical leadership, ensuring successful delivery and mentorship.

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.

Develop and deploy large-scale, fault-tolerant agentic AI systems, lead initiatives, and ensure trustworthy AI agent interactions. Require 5+ years experience and advanced degree in relevant fields.

Lead the Prediction and Planning teams at Motional, overseeing machine learning initiatives, establishing technical roadmaps, and mentoring engineers. Publish research and collaborate across teams to integrate developments into vehicle platforms.

The VP of Product Development will lead a global engineering team for eDiscovery platforms, focusing on modernization, reliability, and AI integration while managing execution and stakeholder communication.

Lead a team of machine learning engineers and data scientists to develop algorithms for personalized shopping, enhancing client engagement and driving growth through AI and data science.

The role oversees analytical characterization and comparability studies for biologics, ensuring regulatory compliance and leadership in product development.

Design, fine-tune, evaluate, and deploy LLM-driven, user-facing browser features using RAG, embeddings, prompt engineering, and modern ML tooling. Lead end-to-end model lifecycle, run production experiments, collaborate with product and engineering, and document and review work with an emphasis on privacy, latency, and usability.

The role involves developing and improving TTS/Voice Generation models, training, fine-tuning, evaluating speech models, and collaborating across research, engineering, and product teams in a fast-paced startup environment.

The Customer Solutions Manager will engage customers, lead solution adoption, coordinate with internal teams, and ensure customer success in telecom solutions.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The MLOps Engineer will design and maintain the machine learning operations infrastructure, optimize cloud services, and build CI/CD pipelines to support AI products for underground infrastructure management.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.

As a Senior/Staff ML Systems Engineer at Quilter, you'll design and maintain ML infrastructure for automated PCB component placement, manage data pipelines, and lead systems design reviews while ensuring project efficiency and reliability within a fully distributed team.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.