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Architect and develop large-scale, distributed data processing pipelines using technologies like Apache Spark, Apache Beam, and Apache Airflow for orchestration. Proven expertise in Apache Spark, Apache Beam, and Airflow, with a deep understanding of distributed computing and data processing frameworks.
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Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks.
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Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake) Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink.
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As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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We are seeking a highly motivated Machine Learning Engineer Co-Op from July 2024 to December 2024, focusing on Natural Language Processing (NLP) and Computer Vision applications.
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As a Machine Learning Engineer II with CodaMetrix you will help with translating proof-of-concept ideas to product grade solutions. The Machine Learning Engineer II reports to the Director of Architecture.
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A minimum of 2 years of industry or research experience in signal processing and/or machine learning. Create and implement mathematical models and machine learning algorithms for processing big data and extracting valuable insights.
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Strong signal and information processing expertise (statistical signal processing, array processing, signal modeling, linear algebra, probability and random processes, optimization, tracking/data fusion, adaptive signal processing, digital signal processing, information theory.
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Use and maintenance of production capital equipment such as heat-treating furnace, X-ray machine, induction brazing machine, electron beam welding machine, mineral insulated cable swaging machine, MIG/TIG welders, orbital welders, optical microscopes, 3D profilers, and CMM.
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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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The Bioinformatics Scientist is responsible for analyzing antibody selection data from yeast display, implementing machine learning algorithms to enhance data analysis and lead selection, and managing the data pipeline from raw file processing to database storage.
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Expert experience with Hadoop based technology (e.g. Spark) and programming (Python, SQL, PySpark). Solid understanding of Snowflake computing, including its integration with Azure Data Lake, utilizing ADLS as a source for data processing.
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The Senior Machine Learning Engineer will serve as a key technical leader, driving the design, development, and deployment of advanced machine learning applications.
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Refine statistical and machine learning models using advanced algorithms such as natural language processing, experimental design and survival modeling, and leverage findings to offer strategic business insights and guidance.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture designAbility to align AI/ML initiatives with broader business goals and outcomes, understanding how AI can drive value and competitive advantage.
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machine learning apache spark processing electronic medical records jobs Title: engineer in Waltham, MA
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