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Data science, machine learning, optimization models, Master’s degree 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, Using open source frameworks (for example, scikit learn, tensorflow, torch)Primary Location.
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As a research scientist at Adobe, you will be joining a dynamic team of machine learning, deep learning, natural language processing, and computer systems researchers to build the future of digital experiences.
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Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence, and identify opportunities for their application in the streaming industry. Strong proficiency in programming languages such as Python, R, or Java, and experience with data analysis and visualization tools (e.g., SQL, Tableau, Matplotlib.
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Strong understanding of machine learning principles, especially in the context of LLMs. 5+ years of proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch Skills in Java/scala (preferred) Experience building scalable deep learning systems.
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You have successfully partnered with Product, Data Engineering, Data Science and Machine Learning teams on strategic data initiatives. What You'll Do Modernize Signifyd’s Machine Learning (ML) Platform to scale for resiliency, performance, and operational excellence working closely with Engineering and Data Science teams across Signifyd’s R&D group.
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Working experience in Golang is desiredArtificial Intelligence / Machine Learning as it relates to networkingFamiliarity with service-oriented architecture and distributed computing. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation.
$150,000 - $175,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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RELATED JOB OPENINGS: Senior Machine Learning Engineer / Data Scientist Senior Software Engineer - Data Engineering Machine Learning Engineer / Data Scientist Analytics Engineer.
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Java, MATLAB, Go. Research experience and publications in related areas (e.g., computing systems, networking, hardware/software co-design, machine learning) are welcome. PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: FPGA or ASIC-based RTL design and verification, FPGA deployment and programming, FPGA based acceleration of cloud applications, programmable data plane, machine learning training on GPUs and awareness of hardware/software co-design.
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Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
$165,100 a yearExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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BS or MS or PhD in Computer Science or Electrical Engineering with Strong coding and Machine Learning skills and 5+ years of Industry experience. This team crafts and builds evaluation tools, automation frameworks and methodologies that enable product teams across Apple to develop machine-learning solutions that power amazingly intelligent user experiences.
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San Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
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As an MLOps Engineer, you will play a critical role in bridging the gap between data science and production, ensuring our machine learning models are deployed efficiently, reliably, and securely.
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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, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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At least one year of experience in the Machine Learning or AI domain, working with technology infrastructure related to Deep Learning, Large Language Models (LLM), Generative AI (GAI), Natural Language Processing (NLP), or other areas.
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You’re experienced with traditional as well as modern machine learning/statistical techniques, including Regression, Classification, Ensemble Methods, Deep Learning, NLP, and Reinforcement Learning.
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