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Job Description :We are looking for a seasoned Machine Learning Engineer specialized in Large Language Models (LLMs) to drive the development and deployment of cutting-edge AI solutions.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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NLP, LLM, Gen AI Model Deployment: Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability.
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Monitor existing and proposed regulations affecting international trade, including artificial intelligence / machine learning and cloud regulations which impact import / export control regulations.
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Audible Content Data Science team partners with business, technology, and product leaders to solve problems related to Content Understanding, Content Evaluation, and Recommendations, relying on Natural Language Processing (NLP), ML, Deep Learning, LLMs/GenAI. We operate in an agile environment in which we own the life cycle of research, design, model development and, often, deployment.
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Es:Lead the design, development, and deployment of machine learning models to support oncology research and product developme. About Us : We are a leading company that specializes in using artificial intelligence and machine learning to develop advanced diagnostic tools for digital pathology, with a focus on enhancing cancer detection and diagnosis.
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Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Experience in Continuous Integration & Continuous Deployment processes using tools such as Jenkins and spinnaker.
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Utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems; visualize and interpret data and create reports, manipulate data using statistical software, and compare models using statistical performance metrics; and support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses.
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Hands on experience in Mobile: security, app deployment, push notification,platform specific SDLC, UI/UX. Proficient in coding Full Stack Java, Object Oriented Programming and Object Oriented Ontology.
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As a Senior ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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Proficiency in cloud services (AWS/GCP) and familiarity with machine learning training, deployment, and distributed computing frameworks like Spark. This includes a thorough understanding of machine learning frameworks, parallel data processing techniques, and proficiency with large language models (e.g., Llama series), text to image (e.g., Diffusion-Based Models, Diffusion Transformers), and text to video technologies (e.g., EMU series, MagViT.
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ML/MLOps Innovation: Guide the team in adopting and innovating in the areas of machine learning model development, deployment, monitoring, and management. Technical Expertise: A deep understanding of Enterprise Software architecture, design patterns, and modern programming languages coupled with a strong foundation in machine learning algorithms, data modeling, and MLOps practices across the major cloud providers (AWS, Azure, GCP.
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Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Deep knowledge of infrastructure engineering such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments.
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RNN) in a work setting, not just academic projects Hands-on experience in building and deploying machine learning and statistical models using Python, PySpark, Machine Learning libraries, SQL. Experience in computing/programming skills; proficiency in Python, R, and Linux shell script.
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Data Science | Machine Learning | ML Engineer | Engineering | Deployment | Production | Real Time Bidding | Auction | Statistics | Mathematics | AdTech | Advertising | Python | Recommendation Engine | Recommender System | Personalization | Bespoke | Target Audience.
$210,000 a yearFull-timeExpandApply NowActive JobUpdated Today
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