Top Remote Data Engineer Jobs in Austin, TX

Formulate a technical vision and roadmap for analytics engineering at Upstart. Understand data production and consumption to create end-to-end solutions. Educate software engineering, analytics, and machine learning teams on data architecture practices. Partner with analytics squads on decision making for the analytics roadmap.

The Senior Data Engineer at Babylist will be responsible for defining the next stages of maturity in data platforms, with a focus on building and scaling Machine Learning pipelines. They will work cross-functionally to deliver data solutions driving product growth and innovation.

Lead a team of Data Scientists and Machine Learning Engineers to create AI models that enhance business growth. Define strategy, implement AI use cases, solicit requirements, build accurate models, and educate business teams on model outcomes.

Dropbox is seeking a Machine Learning Engineer to design, code, train, test, deploy, and iterate on large scale machine learning systems. The role involves building products alongside a multi-functional team and shaping the direction of machine learning and AI at Dropbox.

Seeking a Machine Learning Engineer to design, develop, and implement Machine Learning algorithms for Cloudflare's security products. Responsibilities include collaborating with Data Scientists, deploying ML models, improving model performance, and contributing to the MLOps platform. Desirable skills include understanding machine learning concepts and experience with Deep Learning and NLP applications.

Full-time Data Engineer position at MK Analytics, responsible for creating and maintaining data pipelines, cleaning and managing large data sets, collaborating with data scientists, and ensuring data accuracy. Remote work with competitive salary and benefits package.

Seeking a Senior Data Scientist with expertise in building machine learning models, deploying models, and creating pipelines. Must have experience with AWS Machine Learning tools, data analysis, statistical modeling, and software engineering. The role involves developing ML models, deploying them, creating pipelines, conducting data analysis, and collaborating with cross-functional teams.