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Big Plus: Experience with large scale data processing & pipeline orchestration tools like Dataflow, Kubeflow, Airflow, BigQuery and Ray. Experience in large-scale deep learning recommendation model training using parallel computing, distributed training frameworks (e.g., Ray Training, PyTorch Distributed), and efficient utilization of hardware resources is a big plus.
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Big Data/Machine Learning Engineer Location: Richmond, VA OR Remote Contract: 12 Months Pay rate: 58/hr “Beware of scams. Job Description: We are seeking a skilled Big Data/Machine Learning Engineer to join our dynamic team.
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Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience of its customers.
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End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark) Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest.
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Experience with cloud computing services such as Microsoft Azure, Amazon Web Services and/or Google Cloud Platform Familiarity with different data science techniques: statistics, machine learning, or cognitive AI. Minimum Qualifications, Knowledge, and Skills Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
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5+ years’ experience in data cataloging and classification, data quality, metadata management, data lifecycle, and Big Data administration. You will build solutions using Large Language Models, AI services, and machine learning and you will be working with application teams to design and implement AI services while meeting Responsible AI standards and best practices.
$194,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Ensure data privacy and compliance standards are met in all data engineering and machine learning initiatives. You will lead the effort in driving our data strategy, to enable the next generations of Machine Learning models to drive our Ad Business.
$323,400 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience with big data pipelines (Hadoop, Spark), AI applied research, industrial recommendation systems, Large Language Models (LLMs) and prompt engineering is a plus. Deploy big data technology and large scale data pipelines.
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Ford's GDI&A department is on the hunt for talented individuals skilled in Machine Learning, Big Data, Statistics, Econometrics, and Optimization. We're looking for exceptional Machine Learning and AI scientists who are eager to engage in all project stages, from problem identification to model deployment.
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Experience with big data systems in production: eg, Spark, Pinot, Presto. About The RoleWe use machine learning and large language models to build software which helps our customers operate their business effectively.
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As a machine learning model engineer of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to develop and deploy a wide spectrum of large-scale machine learning products with real-world impact.
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In this role, you will collaborate with cross-functional teams to analyze complex data sets, design and develop machine learning models, and build scalable solutions. As a Machine Learning Engineer, you will play a crucial role in developing and implementing machine learning models and algorithms that drive actionable intelligence.
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JOB TITLE: Machine Learning Engineer. Experience with big data processing frameworks (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS) is a plus. Proficiency in programming languages such as Python or R, as well as machine learning frameworks like TensorFlow or PyTorch.
$90 an hourExpandApply NowActive JobUpdated 19 days ago - UpvoteDownvoteShare Job
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Data Engineer with experience in Spark, Scala, Python, Java, SQL, and big data technologies, capable of building scalable pipelines, deploying machine learning models, and performing data analysis for optimizing ad campaigns.
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Have built and worked on data pipelines using big data technologies (like Spark, Hadoop, EMR, SQL, Snowflake) This role is on the AI and Machine Learning team, which is responsible for building ML models that power key product experiences on Strava.
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big data learning jobs Title: machine learning engineer
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