Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.

Find novel solutions for conducting open source exploitation in order to identify areas of operational efficiencies for the open source intelligence program. We at Leidos are seeking you, our next Russian OSINT Specialist to provide collection and exploitation of publicly-available information (PAI.

Calhoun International is seeking a qualified Open-Source Intelligence Collector to support an INDOPACOM customer. The OSINT collector conducts research and collection of information available from public, private, and U.S. and foreign Government open-source materials within established security protocols.

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.

A Ph. D. in Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required.

Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.

Experience with Machine Learning/Deep Learning Excellent verbal and written communication skills ACADEMIC CREDENTIALS: Bachelors or Masters degree in computer engineering/Electrical Engineering LOCATION: Austin, TX #LI-SL3 At AMD, your base pay is one part of your total rewards package.

Ideal candidates have a strong publication record in areas including artificial intelligence data mining, machine learning, natural language processing, and/or fields such as cognitive science, learning analytics, and psychometrics.

You will work on open source libraries (such as ) to be used in both on-premises and cloud services (such as Databricks, AWS EMR, Google Dataproc, and Cloudera). 5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg.

Develop data science applications for visual inspection and classification, anomaly detection, predictive maintenance, NLP, or root cause analysis using computer vision, machine learning and deep learning.

Forensic analysis of digital information, Open-Source Intel (OSINT) review/monitoring, available tools both customer provided and open source , and pivoting/researching on previously reported Indicators of Compromise ( IOCs.

Position Description: Radiance is seeking a Machine Learning Engineer who will advance the artificial intelligence capabilities of the National Air and Space Intelligence Center at Wright Patterson Air Force Base. This engineer will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and develop machine learning, data mining and statistical algorithms for pattern recognition and anomaly detection.

Under the supervision of the Executive Director, the GA will assist in developing and supporting programs, events, and special initiatives that advance Chapman University's efforts towards becoming and creating welcoming and inclusive learning environments.

Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in timely manner to automatically tackle the issues or provide recommendations for the next step of solving problem.

Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc. Deep knowledge in statistics and Machine Learning models, deep learning models, NLP, Generative Adversarial Networks (GAN), and other generative models.