Top Remote Machine Learning Engineer Jobs in Austin, TX

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Design and develop edge AI firmware for camera systems, ensuring accurate AI algorithms, collaborating on architecture, and mentoring engineers.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

As a Senior Machine Learning Engineer, you'll lead the design, development, and implementation of ML models to detect risks like fraud and account takeovers, while mentoring junior team members and collaborating with stakeholders to translate business needs into technical solutions.

The Senior Machine Learning Platform Engineer will develop ML models, mentor engineers, optimize systems, and enhance ML infrastructure at Coinbase.

The Senior Machine Learning Platform Engineer will optimize ML pipelines, mentor junior engineers, and improve ML infrastructure, focusing on performance and data quality.

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

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

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 the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

Join a team focusing on end-to-end ML Ops for the insurance sector. Develop and deploy ML solutions, build infrastructure, and solve business challenges using advanced technologies.

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

As a Machine Learning Engineer II, you will design, build, and deploy machine learning systems, optimize existing models, and collaborate with data teams.

As a Staff Machine Learning Engineer, you will design scalable ML systems, mentor engineers, solve complex problems, and optimize models in a fintech environment.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.

The Machine Learning Engineer will work on AI/ML projects, optimizing data systems, supporting cloud migrations, and delivering predictive insights using AWS services.

As a Machine Learning Engineer, you will design, build, and test deep learning features, optimizing computer vision applications while collaborating with the ML team and improving processes.

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 role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

As a Machine Learning Engineer, you'll innovate features for dataset curation, model analysis, and integrations, focusing on Visual AI and open-source contributions.