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Expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and programming languages (e.g., Python, Java). Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes.
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Proficient in Python, Linux, AWS (S3, EC2, RDS), Git, Docker, SQL, Numpy, Tensorflow and/or PyTorch. OpenCV, CI/CD principles, Streaming architecture and serverless concepts, Developing data / ML model regression tests, Computer vision pipelines, Container orchestration ( like Kubernetes or ECS ), ML for mobile/IOT, Model compression techniques, Embeddings and vector search, Incremental and active learning methods.
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5+ years of experience in wide variety of distributed systems and frameworks such as Apache Spark, Kafka, Airflow, TensorFlow , Docker, Snowflake and more. 5+ years of experience in wide variety of distributed systems and frameworks such as Apache Spark, Kafka, Airflow, TensorFlow , Docker, Snowflake and more.
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NET Core, Java, SQL Server, Docker, Kubernetes, AWS, Azure. Develop with a variety of platforms and technologies, such as PyTorch, Tensorflow, Spark,. NET Core, Java, SQL Server, Docker, Kubernetes, AWS, Azure.
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Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (e.g., Docker, Kubernetes, Terraform.
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To complement this team, you will welcome ideas that are different from your own and be skilled at finding and building from common ground. Note: Interns are not eligible for variable incentive awards such as stock-based compensation, retirement plan, vacation, tuition reimbursement or parental leave.
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The VP, Engineering will l ead scaling the global data and software engineering team s in managing the foundational enterprise data platform and creat ing tools and frameworks that enhance data collection and processing, analytics and artificial intelligence , data dissemination , and governance.
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Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow. Spring boot, Microservices, Docker, Jenkins and REST API's experience. Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow.
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AI/ML/Distributed-Systems/Network-Architecture, including experience with one or more AI frameworks (TensorFlow, PyTorch, Caffe). Unix/Linux operating systems especially with virtual containerized environments (docker, conda.
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Strong knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP) Strong knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, Azure, GCP.
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Strong proficiency in programming languages such as Python and ML frameworks such as TensorFlow, PyTorch, or other relevant languages and frameworks. Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to facilitate the deployment and scaling of AI solutions.
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We are very interested in expertise around the subfields of semantic segmentation and instance segmentation and you will be involved in keeping up to date with the latest research papers in these areas and implementing them using platforms like PyTorch or TensorFlow.
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Requires programming Languages: Proficient in Python, R, SQL, and scripting, experience with Deep Learning platforms (e.g., PyTorch, TensorFlow, Jupyter Notebook)d, and Version control using Git.
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Research experience in deep learning, machine learning, graph analytics, and numerical analysis. Enable amazing computing experiences with Intel Software continues to shape the way people think about computing – across CPU, GPU, and FPGA architectures.
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At the Trade Desk, Base Salary is one part of our competitive total compensation and benefits package and is determined using a salary range. At our scale, many off-the-shelf techniques and existing technologies (open source and enterprise) simply don't work.
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