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Rhizome is seeking a Software Engineer who can scale our Data Engineering capacity and contribute to Machine Learning development at the enterprise scale. Exceptional programming skills with Databricks or Apache Spark or Amazon EMR or Cloudera.
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Experience using Apache Spark (PySpark or Scala). The candidate should also have desire to learn and enrich their knowledge in data science, machine learning, and other related fields.
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The Staff Machine Learning Engineer is a versatile role in Behaviors that drives a wide spectrum of applied ML research and development to overcome challenges on urban roads. This Includes Working On a Variety Of Really Exciting Problems Such As The Behaviors Teams at Cruise are responsible for developing machine learning models to enable our AV to drive smoothly and safely around an urban environment.
$183,600 - $270,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are looking for an experienced Machine Learning Engineer to help us in our journey to scale end-to-end neural networks for autonomous driving. Developing and implementing machine learning models and robotics systems to enhance the capabilities of our Autonomous Vehicle stack.
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Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases. Prototype machine learning use cases for use in the product, and work with stakeholders to iterate on requirements.
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This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform.
$192,000 - $260,000 a yearFull-timeExpandApply NowActive JobUpdated 6+ months ago - UpvoteDownvoteShare Job
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
$115,400 - $204,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Our next-generation platform, which combines threat intelligence with machine learning, enables financial institutions and governments to detect cryptocurrency fraud and financial crime at an unprecedented scale.
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Work cross-functionally with product, platform, security, and data engineering teams to unlock new machine learning applications. We build our services over Cash App's ever-evolving infrastructure, and as a senior engineer on the team, you will embrace these changes and scale our tech stack to promote future evolvability.
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Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink. Lead the implementation and optimization of data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
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What you'll be doing Build applications, tooling, and frameworks to improve the productivity of Discord's product, analytics, and machine learning teams, using modern technologies such as BigQuery, Airflow, Kubernetes, etc.
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Our current backend stack is Python, Rust, TensorRT-LLM, Kubernetes, AWS. You will work on designing and implementing machine learning models that drive our recommendation systems, retrieval algorithms, and classifiers.
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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.
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Basic affinity or interest in machine learning/deep learning/artificial intelligence. Crafting internal tools that empower our our Machine Learning team to use to enhance search system quality and data.
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This will be a hands-on / applied machine learning role with a focus on Generative AI, RAG, and document understanding (Taxonomy, Digitization, Classification, Extraction, Validation, etc.
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