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With past experience working in fast-paced tech companies, the ideal candidate will recall a history of success leveraging deep HR subject matter expertise and growing business acumen to deploy the relevant manager coaching, manager/team enablement, and organizational development initiatives to assist in enabling the business to meet mission-critical deliverables.
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Experienced in using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, demand modeling, etc.
$90,000 - $120,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Finally, your passion for continuous learning, diversity, equity, and inclusion will be evident in your leadership, communication and delivery, championing Visa’s culture and growth as an organization.
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Deep knowledge of Artificial Intelligence (AI), Large Language Models (LLMs), Generative AI (Gen AI), Machine Learning (ML), and Applied Statistics. Deep knowledge of Data Science and related technologies (Python, R, scikit-learn, Tensorflow, PyTorch, etc.
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As an AI & ML Solution Architect, you will collaborate with cross-functional teams, design and lead end-to-end AI and machine learning solutions that leverage cloud data architectures. Experience with cloud data warehouses (Snowflake, AWS Redshift, Google BigQuery, Azure Data Warehouse, Databricks Lakehouse, etc.
$106,300 - $235,400 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Expertise across modern cloud AI platforms (Databricks, Snowflake, AWS SageMaker, Azure ML, GCP Vertex AI, Dataiku, etc.) Familiarity with data visualization tools such as Tableau and Power BI. Back-up child care, Pet insurance, a Member Assistance Program, a 529 college savings program, a personal financial management tool, lifestyle management programs and more.
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The ideal candidate is adept at using big data sets and applying machine learning and artificial intelligence techniques for analysis and prediction tools focused on environmental and meteorological applications.
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Two years of experience in deep learning model optimization for mobile devices, CPU (Central Processing Unit) inference and GPU (Graphics Processing Unit) inference. One year of experience conducting distributed training of deep learning models.
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The Big Data platform supports operational real-time event-based processing and compute applications as well as analytics consumption use cases including machine/deep learning. Leverage GPU implementation to enable advanced Machine Learning.
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MPI, compilers, and Deep Learning and/or AI experience. Your contribution will play a vital part in cementing our reputation as a customer-centric company that is committed to excellence at every turn.
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We are seeking a talented and experienced Social Security Disability Case Manager who is passionate about our mission and has a deep understanding of the inner workings of the Social Security Disability office.
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And/or TensorFlow/Py Torch 3 years of experience coding on models that implement natural language translation, image recognition, and sequence to sequence deep learning models. We are seeking a Machine Learning Software Engineer with a history of contributions to commercial optimization and deployment projects.
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PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
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The Machine Learning Experience (MLX) team supports an internally hosted Model Training ecosystem running critical infrastructure for machine learning and data analysis across Capital One. You will get an opportunity to collaborate on the 1000's of models being trained on the platform by 4000+ users and dive deep into the unique engineering challenges we have around compute, data access, security and scale.
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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
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