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And we’re pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence. The Embedded Systems Engineer II will collaborate with global Engineering and Operations teams to apply a platform use approach to all new designs while gathering and implementing design considerations for use in multiple product categories.
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Catapult HLS tool isused by leading hardware design and systems companies for cutting edgesemiconductor chip design in edge computing/automotive/machine learning/wirelessdesign/video, image processing etc.
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TensorFlow, PyTorch, Keras (for deep learning and complex machine learning, including neural networks and advanced AI) AWS SageMaker (for end-to-end machine learning development, training and scalable machine learning in a managed cloud enviornment.
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Data Science & Machine Learning Frameworks. CI/CD Pipelines (for automating deployment and monitoring of machine learning models) Python (for preprocessing, data analysis, machine learning, scripting.
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Should be interested in video, audio, signal processing, robotics, RF, or other advanced areas of embedded systems. Seeking a PCB Design Engineer who is eager to work on challenging, cutting-edge, microminiature, high-speed camera array systems in a small team setting.
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Experience with machine learning and statistical analyses are needed. Scikit-Learn (for classical machine learning) Natural Language Processing (NLP) (for analyzing clinical notes or electronic health records.
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Apache Hadoop or Apache Spark (for big data processing) Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data.
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Data Visualization Tools (e.g., Tableau, Power BI, Plotly) Experience with Epic or Cerner (popular EHR systems in healthcare) Electronic Health Records (EHR) Systems. The successful candidate will have demonstrated competence in developing highly scalable artificial intelligence systems with multiple dependencies across teams.
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Clinical Terminologies (e.g., SNOMED, LOINC) Data Warehousing (e.g., AWS Redshift, Google BigQuery) Docker, Kubernetes, ECS, EKS or AWS Fargate (for containerization and orchestration of data applications and reproducibility.
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ETL Tools (e.g., Informatica, Talend, AWS Glue) Bachelors Degree computer science, artificial intelligence, informatics or closely related field. AWS Bedrock (for accessing pre-trained LLMs and foundation models without managing infrastructure.
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AWS, Google Cloud, or Azure (cloud platforms for scalable computing) SQL-based Databases (e.g., PostgreSQL, MySQL, Microsoft SQL Server) The Data Scientist will be responsible for driving insights from the vast amounts of patient and environmental data available within our data warehouse.
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ICD-10 Coding (for medical diagnosis and procedure classification) HL7 (Health Level Seven International standards for electronic health information exchange) HIPAA Compliance (handling sensitive patient data securely.
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Predictive Modeling (for patient outcomes, risk analysis) NoSQL Databases (e.g., MongoDB, Cassandra) Data Privacy (understanding of privacy laws such as HIPAA, GDPR) Work closely with researcher teams to design analysis specifications, including input data specifications, data cleaning, algorithms, and interpretation of results.
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Data Scientist (Healthcare) 100% Remote. R (for statistical computing and bioinformatics) MATLAB (for algorithm development, though less common in healthcare) Data Governance & Security. AWS Lambda and Step Functions (serverless computing and workflow automation.
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Dimensionality Reduction (e.g., Principal Component Analysis (PCA), Cloud Computing & DevOps Skills. Develop and implement algorithms on existing data warehouse records and identify new external data sources to be ingested to the data warehouse to strengthen analyses.
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machine learning software engineer signal processing jobs Title: power systems engineer
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