Top Remote Machine Learning Jobs in Austin, TX
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Senior Software Engineer in the Central AI team at Atlassian, responsible for building and maintaining core infrastructure for machine learning models and pipelines. Leading projects from design to launch, collaborating with internal teams, and setting expectations. Offering competitive compensation and benefits. Requires 5+ years of experience, fluency in Java/Kotlin and Python, experience in Continuous Delivery, Continuous Integration, and large-scale distributed systems using AWS and Apache Spark.
As a Machine Learning Engineer on the Duo Security ML Infrastructure team, you will participate in designing and building systems to handle ML-powered applications and collaborate with various teams in the Data Science & Engineering organization. Responsibilities include working on high complexity technical problems, developing ML infrastructure capabilities, and supporting running models in production.
The senior engineering manager will lead a team of engineers to build and scale Dropbox's AI offering, Dash. They will be responsible for driving product monetization, fostering a collaborative culture, and providing strategic direction.
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As a Senior Machine Learning Engineer, you will develop production ML systems using Python and technologies like TensorFlow. You'll collaborate with Data Scientists to turn prototypes into customer-facing solutions, provide technical leadership, and build data pipelines for algorithm input. Your expertise will drive personalized learning experiences for Pluralsight's users.
Play a major part in building AI and Machine Learning solutions to transform user experience and workflow efficiency of enterprise services. Collaborate with a team to produce quality software for intelligent enterprise services.
As a Data Engineer at Shipwell, you will contribute to the design, development, and maintenance of data pipelines, optimizing cloud infrastructure, and enabling data access for research projects. Responsibilities include ETL, data integrity standards, and performance optimization. Collaborate with cross-functional teams and contribute to scalable data architectures.
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