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A world-class, tight-knit team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology. Genesis Therapeutics is building a world-class software team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry.
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Machine Learning tools such as Scikit-learn, TensorFlow, Keras, PyTorch, Langchain. We believe that life science product development can be accelerated with industrial strength software platforms to generate, prepare, process and utilize large and complex multi-modal molecular datasets using the best-in-class ML and data science practices.
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Our goal is to deepen insights into customer behaviors and satisfaction using data science, machine learning, and AI. We partner with several teams across Robinhood including: Data, Product, Marketing, Eng, Finance, and Research.
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The Chan Zuckerberg Imaging Institute is seeking an experienced AI/Machine Learning Engineer to support the New Algorithms for Cryo ET Team Leader to create innovative algorithms that addressspecific challenges in computer vision, generating meaningful and high-quality data representations that facilitate downstream tasks.
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Experience with supporting data science / machine learning data pipelines. Due to the hybrid requirement at this point we are looking for an exceptional software engineer, confident in data platforms.
$180,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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You are an individual with a deep understanding of computational genomics, bioinformatics, machine learning, statistics, next-generation sequencing, and single-cell multi-omics. Develop novel machine learning algorithms to get biological insights from the multifaceted genomic datasets.
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A Day In The Life Of Our Software Engineer. Life Insurance (company paid & supplemental) and Disability insurance. Learning & Development Opportunities: On-demand online training and book reimbursement.
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Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. Work as a full stack engineer for both robot software as well as backend server side software development using AWS cloud.
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The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, and operational excellence to empower a broader, more diverse audience of drone users - from first responders to insurance claims adjusters, utilities, and more.
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Entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers. We want Data Science/Machine learning/Data Analyst and Java Full stack candidates.
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Relevant industry experience is important (Site Reliability Engineer, Systems Engineer, Software Engineer, DevOps Engineer, Network Engineer, or similar role), but ultimately less so than your demonstrated abilities and attitude.
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Any experience of the following is useful too: Cisco Data Center Nexus, Cloud, Cisco ASA/PIX, Cisco Secure, ACS, Cisco ACI, Cisco IronPort, Checkpoint FW-1 and NG, Juniper Netscreen and SRX, Palo Alto, Bluecoat and Fortinet security hardware/software products.
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Submits Insurance claims to Safety Engineer. Advanced knowledge of Prolog software. Performs work tasks by receiving direction and then working independently with an interest in quickly learning and applying new skills and abilities.
$180,000 - $215,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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Software Engineer - Communications Suite. Software Engineer - Fullstack. DSP Engineer (Radar) Array Labs is building a distributed radar imaging constellation to power the first accurate, real-time 3D map of the world.
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