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Participating in INT Functional Management meetings related to Open-source intelligence (OSINT), Measurement and Signature Intelligence (MASINT), and Human Intelligence (HUMINT), as well as ISR Collection, ISR capabilities and ISR Data Integration tasks related to IC and International partnership.
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Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. As a Machine Learning Engineer on the Banking & SFS team, you will support fellow Data Scientists and Modelers in building and deploying machine learning models that support our banking and lending business.
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The candidate will be working with the following state of art technologies; Solr, Lucene, Natural Language Processing, Machine Learning, Linux, Groovy, Python, Splunk, Prometheus, Grafana, DevSecOps, Jenkins, Maven, Gitlab, Nexus, Ansible, TDD, BDD, JMeter, Selenium, and other open source frameworks.
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Minimum of 3 years of hands-on data analysis experience in full-time professional, data-heavy, and machine learning focused role. Experience developing and deploying machine learning and statistical models.
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TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution. NOTE: There is a strong preference for this role that candidates live in the San Francisco Bay Area and be open to 1-2 days of in-office work per week in either our San Francisco or Oakland office locations.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Expertise in open source data science technologies such as Python, R, Spark, SQL. Strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods.
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Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch. Understanding of containerization technologies like Docker for packaging machine learning models and deploying them in production.
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Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment. Knowledge of data preprocessing, feature engineering, and model evaluation techniques in machine learning projects.
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Join us as a Senior Machine Learning Engineer specializing in Natural Language Processing (NLP), where you will tackle some of the most exciting challenges in the field today. This role involves working with state-of-the-art machine learning and deep learning algorithms, focusing on next-generation AI technologies such as large language models, generative AI, retrieval-augmented generation, LLM agents, and fine-tuning techniques.
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Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
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Strong expertise in generative AI techniques for summarization, Chatbot and data embedding using AWS, Microsoft Azure Open AI and other open source LLM models. Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
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AWS Certified Solution Architect – Professional (and/or) AWS Certified Machine Learning Specialty. Expertise in designing and developing software applications in java and python including experience with microservices (spring boot and/or Flask.
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Senior #Machine #Learning #Engineer #Modeling #Financial #Crimes #Technology. Senior Machine Learning Engineer (Modeling), Financial Crimes Technology. Build both batch and real-time machine learning solutions for the assessment of financial crimes risk at scale across all global markets in which Square operates.
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As a Full Stack principal engineer, you will work on the front-end, API, middleware and back-end architecture, design, coding using various languages, evaluate and use different development frameworks including microservices architecture and DB design, third-party and open-source software and libraries.
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machine learning open source jobs Company: Birlasoft
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