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The Machine Learning Engineer role requires experience in Azure OpenAI, Large Language Models (LLMs), Python, and proficiency in developing applications using Streamlit, LangChain, Databricks, and Python frameworks like Flask and FastAPI. The ideal candidate will be adept at building scalable machine learning models and deploying them to production environments, and also being part of customer success teams.
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At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
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At least 6 years of experience with machine learning and backend engineering. Our current backend stack is Python, Rust, TensorRT-LLM, Kubernetes, AWS. You will work on designing and implementing machine learning models that drive our recommendation systems, retrieval algorithms, and classifiers.
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Experience as a Machine Learning engineer building feature engineering pipelines, deploying AI models, and optimizing model inference. Design and develop machine learning and deep learning systems using appropriate ML algorithms/frameworks.
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As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
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And we’re pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence. The Embedded Systems Engineer II will collaborate with global Engineering and Operations teams to apply a platform use approach to all new designs while gathering and implementing design considerations for use in multiple product categories.
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Requirements: Must have a Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related field and 2 years of experience as a Software Engineering Intern, Application Engineer Intern, or related.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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MBRDNA is headquartered in Silicon Valley, California, with key areas of Autonomous Driving, Advanced Interaction Design, Digital User Experience, Machine Learning, Customer Research, and Open Innovation.
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Minimum of 2 years’ experience as an Electrical Engineer, Avionics Engineer, or Electronic Engineering. Knowledge of electrical design tools such as Keysight Advanced RF Design Systems, PSpice Analog & Digital circuit analysis, APL or MATLAB and PCB schematic, layout & Gerber editors.
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The HDRDP leverages state-of-the-art technologies, including advanced sensors, robotics, and machine learning algorithms, to improve the accuracy and efficiency of mine and UXO detection.
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From Amazon.com to world class machine learning pipelines, from cutting-edge digital healthcare to no-checkout retail, we push the boundaries of technology in every direction using the globe’s largest AWS deployment.
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About the role As a Staff Machine Learning Engineer at Ladder, you're an integral part of our engineering team playing a critical role in designing, developing and deploying advanced machine learning models to transform the life insurance industry.
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PhD or equivalent experience in Applied Mathematics, Audio Engineering and Signal Processing, Acoustics, Electrical Engineering, Computer Science, or a related field. Develop novel algorithms and signal processing techniques to solve complex problems at the intersection between beamforming, machine learning, acoustics and signal processing with applications in VR and AR.
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Statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering). We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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