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Collaborate with Product and backend engineering teams to ship high-impact featuresRequirements: 4+ years of experience in machine learning engineering with production systems using Scala, Python, and Apache Spark Experience owning recommendation or search models MSc or PhD in Computer Science, Statistics, Applied Mathematics, Physics, or other technical field.
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Experience in one or more of the following: computer vision (e.g. tracking, pose estimation, action recognition), computer graphics (e.g. appearance, geometry, physically-based modeling), robotics (state estimation, optimal control), machine learning (e.g. efficient deep learning, domain adaptation, transfer learning), natural language processing, or human-computer interaction.
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As a Machine Learning Engineer on the Banking & SFS team, you will support fellow Data Scientists and Modelers in building and deploying machine learning models that support our banking and lending business.
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Experience in designing and implementing infrastructure for machine learning pipelines using Apache Spark or Apache Flink. Evidence that elite defenders use to proactively hunt for threats, accelerate response to cyber incidents, gain complete network visibility and create powerful analytics using machine-learning and behavioral analysis tools.
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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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Develop machine learning and statistical modeling algorithms to facilitate biomarker and target discovery. Demonstrated expertise in the development of machine learning and statistical modeling algorithms.
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All of that data that we process goes through Machine Learning and Deep Learning algorithms and models, all built and trained in-house, to ensure peak relevancy for consumers, and are constantly being improved upon, which results in one of the most advanced and mature Machine Learning practices in the world.
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Nobell is seeking a Computational Biologist / Machine Learning Scientist to join our team of scientists to contribute to the development of the Nobell Plant Grown Protein (PGP) platform.
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Our platform is an essential piece of the daily work for machine learning engineers, from academic research institutions like FAIR and UC Berkeley to massive enterprise teams including iRobot, OpenAI, Toyota Research Institute, Samsung, NVIDIA, Salesforce, Blue Cross Blue Shield, Lyft, and more.
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And machine learning and deep learning frameworks (e.g. TensorFlow, Keras, PyTorch) We are seeking a highly motivated scientist with expertise in digital pathology, including image acquisition and analysis using cutting edge deep learning technology.
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The Difference You Will Make: As a Staff Machine Learning Engineer on the Account Integrity team, you will be working with data scientists, designers, product managers, and customer service operations to innovate new ways we can stop bad actors in the ever evolving fraud landscape across team boundaries.
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PhD in Machine Learning, Computer Science, Computational Biology, or related field or equivalent industry experience (2+ years) We leverage functional genomics, pooled perturbation screening, and machine learning models to unravel the biology of epigenetic aging and disease using experiments of unprecedented scale.
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Experience using machine learning libraries or platforms, including Tensorflow, Caffe, Theanos, Scikit-Learn,or ML Lib for production or commercial products. ● Design and implement end-to-end solutions using Machine Learning, Optimization, and other advanced computer science technologies, and own live deployments to drive advertising conversion.
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Machine Learning is an integral part of how we design products, operate, and pursue Cash App's mission to serve the unbanked as well as disrupt traditional financial institutions. Check out our Machine Learning / AI blog here.
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The Digital Pathology Principal Scientist will be accountable for implementation of digital pathology including image analysis and artificial intelligence/machine learning (AI/ML) algorithms for clinical trial biomarkers including pharmacodynamic, mechanism of resistance, patient selection and biomarker discovery.
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machine learning jobs in San Francisco, CA
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A Potential TikTok Ban?!
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The Effects of Workplace Racism and Sexism
One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
When Rage Applying Strikes: How to Identify Unserious Candidates
As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
How to Increase Job Ad Exposure
In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.