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Expertise in machine learning frameworks, including TensorFlow or PyTorch, and the ability to leverage them for custom solutions. A minimum of 6 years of experience in designing and implementing complex AI and ML solutions, as a Senior Data scientist, Machine Learning Engineer, or AI Engineer.
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Senior Staff Machine Learning Engineer. Production experience implementing, maintaining, and improving machine learning pipelines and models at scale in Python, Java, Scala, or similar languages.
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Proficiency in developing deep-learning models using PyTorch, JAX, or TensorFlow. Expertise in the internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.
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Key Responsibilities:- Design, develop, and deploy advanced machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch and TensorFlow. - Extensive experience with machine learning frameworks like PyTorch and TensorFlow.
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Experience with deep learning and machine learning libraries including PyTorch, TensorFlow, Keras, and scikit-learn. Experience utilizing CUDA and NVIDIA GPU accelerated libraries for AI, machine learning, and deep learning tasks.
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Optimize machine learning algorithms and infrastructure for performance, scalability, and cost-efficiency. Deploy machine learning models into production environments, ensuring scalability, reliability, and real-time performance.
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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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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.
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Collaborate with leadership, product managers, customer success staff, and other teams to align machine learning initiatives with business goals. This involves harnessing cutting-edge generative AI alongside traditional machine learning methodologies.
$187,000 - $299,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Net, C#, Android SDK, Kotlin, IOS Swift, AWS: EMR, S3, Redshift, Athena, Glue, DynamoDB, Lamda, CloudWatch, ElastiCache, Kinesis, SNS, SQS, Azure: HDInsight, Data Factory, Data Lake Analytics, Databricks, GCP, and Big Data Apache: Hadoop, Hive, Hue, Sqoop, Kafka, Spark, Airflow, SnowFlake, Python, Scala, Machine Learning: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Apache Mahout, Vertex AI, Keras, OpenNN, Theano.
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Experience in AI, Python programming and one of the following Deep Learning frameworks, PyTorch, MXNet, TensorFlow, Keras, and big data te chn ologies like Hive, PySpark, Synapse, and Databricks.
$153,400 - $285,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines. Sr. Machine Learning Engineer. You are familiar with applied data science methods, feature engineering and machine learning algorithms.
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Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, Machine Learning Scientist III (NLP) Preferred: 4+ years of experience in NLP, Data/Machine Learning.
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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications within The Friedkin Group of companies. Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP.
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Experience in supporting Deep Learning, Machine Learning or HPC networking infrastructures; experience with networking technologies as well as understanding deep learning frameworks such as TensorFlow or PyTorch.
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