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We are a deeply mission-driven company, working hard to develop tech that revolutionizes teacher professional learning - and we’re looking for an Engineering Manager who wants to use their skills to power our mission.
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We’re looking for a Machine Learning Engineer who will build out and design machine learning infrastructure for a team of data & remote sensing scientists, working collaboratively with the Analytics and Software teams to deliver data-driven products and solutions.
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The Opportunity at Altana The Engineering team is looking for talented Machine Learning Engineers to help build out our vision. 6+ years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions.
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This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Share your passion for writing high-quality code, staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community.
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As a Senior Machine Learning Engineer, you will work on a broad set of domains that power a data-driven transformation of our standard business procedures across channels. This is an opportunity for a Senior Machine Learning Engineer to come in and drive the operationalization of AI/ML initiatives for the enterprise.
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The Engineering team is looking for talented Machine Learning Engineers to help build out our vision. 10+ years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product-oriented ML solutions.
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The adjacent areas of major focus are Machine Learning Infrastructure and workflow, Experimentation Platform, Knowledge Graphs and various Data Science and Analytics related tooling. You will report into the Senior Director of Engineering, Data Platform as part of our Data organization in Engineering.
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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency.
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Deep understanding of Machine Learning best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, personalization and recommendation.
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As an early hire, you will contribute to the development of machine learning models and infrastructure needs across the Attentive platform and work with Product Management and Engineering to implement end-to-end modeling use cases.
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Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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Collaborate with the engineering team on implementation and deployment of new algorithms and machine learning models to production. SiriusXM is looking for a senior applied science leader to join our Science and Machine Learning.
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You will be fully remote and report to the Data & Machine Learning Platform Engineering Manager. Senior Software Engineer, Privacy Engineering Block is Square, Cash App, Spiral, TIDAL, TBD, and our foundational teams.
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Solid Machine Learning Engineering background and familiarity with state-of-the-art deep learning techniques especially for NLP. Experience working with Sagemaker, Tensorflow, Pytorch, Triton, Spark, or equivalent large-scale distributed Machine Learning technologies on a modern containerized deployment stack using Kubernetes, Spinnaker, and other technologies.
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Working closely with our data engineering team, you'll design and implement an enterprise-grade machine learning infrastructure focused on credit risk modeling and fraud detection based on blockchain data.
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