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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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Cloud Certifications, such as AWS Certified Solutions Architect, AWS Security Specialty Hands–on experience in offensive security, and CVEs to prove it. Qualifications: Deep expertise in at least one domain: web application and browser security, mobile application security, applied cryptography, machine learning and artificial intelligence security, offensive security, cloud security, hardware security.
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Familiarity or hands on experience with Secure Cloud Development. Rhizome is seeking a Software Engineer who can scale our Data Engineering capacity and contribute to Machine Learning development at the enterprise scale.
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In this role you will:Train, tune and validate machine learning models using Tensorflow, Python and GCP cloud infrastructure. Knowledge of programming and machine learning tools including Python, SciPy/NumPy/Pandas, TensorFlow, Git and cloud computing platforms.
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You’ll join the team that improves user engagement and revenue generation by leveraging machine learning, cloud platforms and big data to combat fraud, improve member experience, create user recommendations and much more.
$180,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Relevant certifications in AI/ML, cloud computing, or related technologies may be beneficial, such as Google Cloud Professional Data Engineer, AWS Certified Solutions Architect, etc.
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Job Summary:We are seeking a hands-on software engineer to join our team and drive development and deployment of Applied Machine Learning capabilities into our platform, such as Semantic Search, improved Recommendations, improved Text processing and Translations, and possibly a conversational interface.
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Hands-on experience with AWS cloud services, including Databricks/Spark, Terraform, Docker containers, ECS, CloudFront, DynamoDB, S3, and Kinesis. Utilize AWS cloud services, including S3, Databricks/Spark, CloudFront, DynamoDB, ECS, Kinesis, to build scalable and resilient solutions.
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Data Architecture & Tools: modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI (Python, R, Jupyter Notebooks, data wrangling, machine learning.
$242,830 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Proven experience in applying traditional machine learning methods as well as, Deep Neural Networks, Generative AI and LLM on data from pharmaceutical or other industry sectors. Experience with linux and high-performance or cloud computing environments (e.g., AWS) and data lake platforms (e.g., Databricks.
$259,400 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Extensive hands-on experience implementing serverless real-time/near real-time architecture using Cloud native services (i.e., Azure, AWS or GCP Tech Stack), and Spark technologies (e.g., Spark Streaming, Spark ML.
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Experience with machine learning algorithms and frameworks such as TensorFlow, Keras, PyTorch, Scikit-Learn, Knowledge of cloud computing platforms such as AWS, Azure, Google Cloud.
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Senior Machine Learning Engineer AtanAI Boston, MA, Brooklyn, NY, San Francisco, CA, Washington, D.C., Remote, London, England 11-10-2023 HealthTech Azure Elasticsearch Docker AWS Python Machine Learning Expires in: -5 days Subscribe and find similar jobs: Altana provides the world’s only dynamic, intelligent map of the global supply chain - the Altana Atlas - using AI and machine learning models to connect with and learn from massive sets of public and private data.
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Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performance. Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, and cloud services (both GCP & AWS.
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As a Machine Learning Modeler on the Fraud Risk Team, you will be responsible for developing and implementing machine learning models to detect and prevent fraudulent activities.
Full-timeExpandApply NowActive JobUpdated 3 days ago
machine learning hands on aws cloud jobs Title: engineer Company: Grotech Search in San Francisco, CA
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