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Deep knowledge in the Machine Learning and data space including designing, building, optimizing and scaling data-intensive Client solutions using distributed computing. Expertise in Python and SQL, with working experience in Apache Spark, Hadoop, Databricks, Snowflake, or other big data systems.
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Data Movement (Apache Spark, plus Azure Data Factory and legacy SSIS) Additional Preferred Experience Machine Learning/AI Practitioner expertise, including. Knowledge of Databricks development, including Scala, Python, and Spark.
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You will design, implement and deploy high-performing machine learning/AI models and create API endpoints in AWS or Databricks. A little about ADP: We are a global leader in HR technology, offering the latest AI and machine learning-enhanced payroll, tax, HR, benefits, and much more.
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Knowledge of Deep Learning and Machine Learning techniques, and experience in Machine Learning tools, techniques and programming (including LLM - Large Language Models) is a plus.
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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.
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Experience with machine learning, specifically in the domain of natural language processing (NLP). As a key member of the Standardized Operations and Analytics group, this position will have a keen interest in applying statistical analysis, data mining, and incorporation of machine learning and predictive analytics into real-world operational processes, especially in forecasting, staffing optimization, and process design.
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Ideal candidates will also have experience in statistical signal processing and its application to sensor data or experience leveraging the latest techniques in deep learning for computer vision.
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Provide technical excellence to apply state-of-the-art machine learning / artificial intelligence utilizing technologies such as Spark, R, Hadoop, Scala, SQL to real world infrastructure business problems.
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The Role We're looking for a senior machine learning engineer to join our growing world-class engineering team. The role will be responsible for all aspects of our machine learning, including data processing, model development and implementation.
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Design and implement robust and scalable Machine Learning solutions, leveraging cutting-edge AI techniques, deep learning algorithms, and natural language processing capabilities.
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Pluralsight is hiring a Senior Machine Learning Engineer in our Draper, UT office. As an experienced machine learning engineer, your expertise will be vital to solving sophisticated problems and building the algorithms and frameworks that accelerate our personalization capabilities.
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As we continue to build our Data and ML capabilities to deliver the promise of helping our customers unleash the power of their data and bring the trades industry at AI parity with other technology enabled industries, we seek to add a Senior Machine Learning Engineer with deep technical expertise in Machine Learning, ML Infrastructure, productionalizing ML workflows and Deep Learning approaches including Large Language Models and Generative AI.
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AWS Cloud, Ansible, Apache, Apigee, Appium, Brakeman, CenOS, Docker, FastLane, Git/Enterprise GitHub, Groovy, Java, JavaScript, Jenkins, Jira, JUnit, JSON, Kafka, Kubernetes, mySQL, New Relic, OpenSSL, PKI, PostgresSQL, Python, Ranger, RVov, React.
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Experience with data processing frameworks (Apache Spark preferred) Practical experience with Machine Learning on Kubernetes. Experience building and maintaining machine learning platforms and pipelines.
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Deep knowledge of how organizations effectively and responsibly adopt advanced technologies, such as artificial intelligence (AI), machine learning, and quantum computing. Serve as the trusted legal and strategy advisor to enterprise efforts to responsibly adopt emerging technologies by providing thought leadership on the legal implications of digital solutions.
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