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Hadoop, HDFS, Teradata, snowflake, AWS cloud, Hive) Solid understanding of advanced statistical methods and machine learning techniques: GLM/Regression, Random Forest, Boosting Trees, Neural Network, Clustering, KNN, Anomaly Detection etc.
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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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Hands-on experience working on AWS Cloud Based applications development using EC2, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, and Kinesis. Develop solutions using AWS Cloud Services for compute, storage, databases, and security and Azure Services.
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Implement cloud-based solutions leveraging AWS services such as EC2, S3, Lambda, RDS, DynamoDB, etc. Experience developing and deploying applications on AWS cloud infrastructure. This role focuses on implementing AWS cloud solutions and building RESTful APIs to support diverse client requirements.
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To implement integration logic and a strong fundamental understanding of data structures Proficient in SQL Exposure to machine learning execution and related analytical tools Knowledge of cloud deployment processes, and experience working in a mature DevOps environment Analytical, curious, open-minded, and passionate about exploring and solving problems.
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Job Summary:This position will work with cutting edge technology, deliver high quality solutions across various industries, and oversee team(s) on engagements that range in size and scope.
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One or more years of experience and proficiency in AWS Cloud Service, Python and Sql for data profiling, analysis and extraction. Build and support the operation of Cloud and On-Premises enterprise data infrastructure and tools.
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You Will Work As Part Of Our Enterprise AI Team And Build Systems That Will Enable Our Users To Work With Large-Language Models (LLMs) And Foundation Models (FMs), Using Our Public Cloud Infrastructure.
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Reconcile and perform data analysis between the Firm’s financial systems (e.g., general ledger) and CARI as well as CARI to other data warehouses leveraging Essbase, SQL and future AWS Cloud tools.
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Design and build run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud. You will work on a wide range of initiatives, whether that's building large-scale distributed training clusters, or deploying LLMs on GPU instances for real-time applications and decisioning systems, or supporting cutting-edge AI research and development, all in our public cloud infrastructure.
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Expertise with cloud computing technologies (AWS, Kubernetes, etc.) The successful candidate will own and manage large and complex technical deliveries that are critical to the success of the Liquidities business along with owning technology transformation of the underlying platforms to cloud native and micro-services architectures.
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Based in Tampa, Florida with a strong presence in Colombia, Argentina, and across LATAM, we give our clients in North America access to onshore and nearshore tech talent, to build digital pods or deliver projects to help drive innovation, from Full Stack Software Engineering and Digital/Cloud Modernization to a growing practice on Data Engineering and AI.
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