Top Remote Machine Learning Jobs in Tucson, AZ

Responsible for building scalable microservices and data pipelines, mentoring junior engineers, and ensuring data quality for ML training.

Lead a team of ML engineers and software engineers focused on Ads Content Understanding, driving innovation and efficiency in Ads Monetization.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

As a Senior ML Ops Engineer, you'll automate, monitor, and scale machine learning workloads, manage infrastructure, and collaborate with teams to productionize AI services.

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

Design and optimize ML models for AI-powered facial analysis, focusing on computer vision and generative models, ensuring accuracy and efficiency in a B2B SaaS environment.

Seeking a senior product designer for AI/ML platform development, responsible for transforming user experiences, leading projects, and mentoring designers. Emphasis on design impact and collaboration with cross-functional teams.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As a Senior Applied Machine Learning Engineer at Upwork, you'll leverage advanced machine learning techniques to enhance search and recommendation systems, analyze data to improve user experience, and develop large language models.

The Senior Machine Learning Engineer will lead ML initiatives, design scalable systems for data processing, and mentor colleagues to build robust ML infrastructure.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.

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

Lead the development and deployment of machine learning solutions that enhance content discovery on Netflix, partnering with engineering and creative teams.

Design, build, and maintain distributed training infrastructure for Ads ML models, while collaborating with ML engineers to optimize training processes.

Design and maintain scalable ML models for logistics. Own end-to-end projects and collaborate with teams to deliver impactful customer features.

As a Sr. Software Engineer, lead the development of AI-powered systems for Payment Integrity. Collaborate with teams, mentor engineers, and enhance system reliability while processing large-scale unstructured data.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

Develop optimization algorithms for ad personalization, integrate ML model predictions, translate findings for stakeholders, and A/B test features.

As a Principal Data Scientist, you will analyze complex data, create measurement techniques, collaborate with teams, and develop models to enhance Zillow Rentals' marketplace performance.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

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.