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We are looking for a hands-on machine learning engineer who is passionate about crafting, developing, and deploying cutting edge AI/ML solutions which will impact millions of customers. Familiarity with one or more deep learning software frameworks such as Tensorflow, PyTorch.
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Ph. D. in Computer Science, Artificial Intelligence, Machine Learning or related field; or M.S. in related field with 3+ years experience applying machine learning engineer to real business problems.
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Deploy machine learning models to cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure. 15 or more years of experience with a Bachelor's Degree or 12 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, or MD), PhD with 9+ years of experience in computer science, computer engineering, mathematics, or equivalent field with a focus on artificial intelligence/machine learning.
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Machine learning libraries: TensorFlow, PyTorch, Scikit-learn, Deploying and optimizing different pipelines that support various data science processes. Machine Learning Engineer with 7+ years of experience in designing, building, and maintaining machine learning models and pipelines.
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Developing and deploying Spark/Databricks jobs with enterprise tool stack including Jenkins, GitHub Actions. Experience with AWS cloud services and running Apache Spark applications. Experience with API development leveraging Fast API / Flask.
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San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
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Machine Learning Optimization: Design, implement, and maintain machine learning algorithms to optimize the operations of renewable energy projects. The successful candidate will play a crucial role in optimizing the operations of renewable projects through the application of machine learning algorithms.
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Advanced degree, ideally a Ph. D., in Computer Science, Electrical Engineering, or a related field with specialized research in areas such as machine learning, NLP, Large Language Models (LLMs), multi-modal foundation models, and generative AI techniques.
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A Staff Machine Learning Engineer on the Striveworks Engagements Team (professional services) is customer-facing and executes with the agency of exceptional technical creativity. As a Staff Machine Learning Engineer (MLE) at Striveworks, you will be challenged—and trusted—on day one to take ownership of machine learning projects that impact a diverse set of Striveworks’ customers.
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You have a BA/BSc degree in Computer Science, Machine Learning, Electrical Engineering, or related technical field. You have at least 3 years of commercial experience developing and productionizing real-time projects in Machine Learning and Data Science.
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You will work on the forefront of technology, applying your expertise in computer vision, machine learning, and sensor fusion to create robust and reliable perception solutions that enable our ASVs to navigate and make critical decisions in complex maritime environments.
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CoreWeave builds cloud solutions for compute intensive use cases — VFX and rendering, machine learning and AI, batch processing, and Pixel Streaming — that are up to 35 times faster and 80% less expensive than the large, generalized public clouds.
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Apply machine learning, image processing & statistics to problem solving. Are you a Senior Data Scientist with geospatial and remote sensing experience looking to work for an exciting start-up company who offer excellent hands on training and structured progression.
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Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types.
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Strong understanding in the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Ray, LangChain, Data lake house (Databricks), Snowflake, SageMaker, Scikit-learn, etc.
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machine learning jobs in Austin, Plainfield, Indiana
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Hiring Transparency
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