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Lead Machine Learning Engineer - Semiconductor. Machine Learning | Semiconductor Manufacturing | AI | Electrical Engineering | Automation | MLOps | Java | C. Lead the development and deployment of machine learning algorithms for semiconductor manufacturing challenges.
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Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Design, develop and deliver scalable, robust and highly re-usable components using technologies such as Python, Java, AWS serverless (Lambda, Glue), Apache Spark, Apache Kafka and REST.
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PhD and 2+ years of relevant research experience in developing machine/deep learning-based solutions and a sincere interest for computational life sciences. The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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We are seeking a collaborative bioinformatics and machine learning scientist to join the Computational Design and Predictive Modeling team in Cambridge, MA. You will develop novel bioinformatics and machine learning solutions and apply them to next-generation sequencing (NGS) data to discover and characterize biotherapeutics.
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The successful candidate will have a strong conceptual/theoretical and practical/hands-on background in mathematics, physics, artificial intelligence, machine learning (including deep learning), or related area and is highly motivated to contribute to scientific and engineering advances in a fast paced, high caliber, entrepreneurial academic setting.
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Design and develop scalable data pipelines using tools like Apache Spark and Kafka. Familiarity with data warehousing solutions (Snowflake, Redshift). We are an innovative technology company revolutionizing data solutions.
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Field of Study/Additional Specialized Training: Preferably in medical physics, computer science, bioengineering, mathematics, statistics, neuroimaging, or related field; Hands-on experience designing, developing, implementing, and validating software solutions, with a focus on neuroimaging, neuroinformatics and machine learning applications.
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Lead the engineering team in designing, developing, and deploying solutions applying modern web frameworks, machine learning solutions, data engineering technologies, microservices, and cloud-native architecture.
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Fidelity’s Financial Intelligence Unit (FIU) is seeking a motivated Squad Leader/Product Owner with a passion for building business critical Fraud Prevention capability, using a range of data science, machine learning, software and data management technologies and tools.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Proactively problem solve, formulate problem statements and sets, derive them to manageable data collections and apply critical thinking to develop solutions.
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What you will be responsible forDevelop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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Minimum of 3 years of building and operationalizing large-scale enterprise data solutions using one or more third-party resources such as Pyspark, Talend, Matellion, Informatica or native utilities as Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache, Beam Composer, Big Table, Cloud BigQuery, Cloud PubSub etc.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. You'll make valuable contributions from day one by continuously learning, engaging in diverse sets of experiences, and building close-knit relationships across the company.
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Applicants should possess a PhD in a relevant discipline (computer science, machine learning, epidemiology, electrical engineering, or applied mathematics) and have established an excellent research profile in signal processing or machine learning.
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Master’s degree in Data Science, Bioinformatics, Computational Biology, Machine Learning, Statistics, Mathematics, Physics, and 3+ years of professional experience. The successful candidate will work at the interface of data analytics, data mining, statistics, bioinformatics, and machine learning with broad impact across early discovery, candidate development, and biomarker discovery.
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machine learning apache spark jobs Title: solutions architect Company: Databricks in Boston, MA
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