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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Have expertise in Machine Learning best practices (e.g. model evaluation and hyperparameter tuning, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection.
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Familiarity with popular python machine learning libraries such as PyTorch, Tensorflow, and Hugging Face. The OpenShift AI team is looking for a Senior Software Engineer with Kubernetes and Machine Learning experience to join our rapidly growing engineering team.
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Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML etc. New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Machine Learning Engineer San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Lead Machine Learning Engineer Remote (Regardless of Location): $170,700 - $194,800 for Lead Machine Learning Engineer.
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Expertise in machine learning toolchains and techniques, such as Pytorch or Tensorflow. Whether it’s holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.
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As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
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Experience working with Research Scientists, reading technical research papers, and implementing state-of-the-art methods in Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Knowledge Representation and Management, etc.
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5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing. 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
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Machine Learning (50%): Iterative model development ML data preparation – cleansing, transformation Model validation, hyperparameter tuning Model building and prediction runtime performance optimization.
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The compiler stack, DL graph optimizations, and kernel authoring for specific hardware, directly impacts performance and deployment velocity of both AI training and inference platforms at Meta. You will be working on one of the core areas such as PyTorch framework components, AI compiler and runtime, high-performance kernels and tooling to accelerate machine learning workloads on the current & next generation of MTIA AI hardware platforms.
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AWS or GCP) and developing machine learning models in a cloud environment. Strong high-level programming skills (e.g., Python), frameworks and tools such as Pytorch, kubernetes, TensorFlow, etc.
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Ideally, you are familiar with modern machine learning frameworks such as TensorFlow or PyTorch. Perso Engine is an enablement organization that enables over 20+ product engineering teams across Etsy to leverage machine learning in building recommendations, personalization, and discovery products.
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Role and Responsibilities:As a Senior AI/ML Engineer, you will be at the forefront of developing cutting-edge solutions that leverage artificial intelligence and machine learning technologies.
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Research experience in deep learning, machine learning, graph analytics, and numerical analysis. AI/ML/Distributed-Systems/Network-Architecture, including experience with one or more AI frameworks (TensorFlow, PyTorch, Caffe.
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You will be expected to own the technical side of relationships with Data Science/Machine Learning Engineering leadership at prospective clients, be diligent and detail-oriented in guiding them from technical discovery through structuring and executing an evaluation or proof of concept.
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