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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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You will contribute to developing machine learning modeling and prediction pipelines using multi-modal biomarker data from clinical trials. Join our team and leverage your expertise to develop state-of-the-art machine learning models and prediction pipelines using multi-modal biomarker data from clinical trials.
$89 - $91 an hourFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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The incumbent will apply advanced data analysis skills and machine learning in collaboration with a group of computational and biological scientists to perform translational oncology research around multimodal translational data sets for programs in clinical development.
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How you’ll make an impact:Lead and drive the development of data engineering technology and platforms for the company's data needs, ensuring their reliability, performance, and flexibility.
$181,000 - $241,000Full-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Our machine learning systems monitor and surface suspicious activity (money laundering, illegal activity and terms of service violations) for agent review. Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performance.
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Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performanceUse Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP & AWS) to get the job doneQualificationsYou Have: 5+ years of Machine Learning modeling experience.
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Apply mathematical (geometry, linear algebra, numerical methods, error analysis) and machine learning methods to prototype and develop algorithms for converting raw depth sensor data into point clouds, 2D and 3D tracking like SLAM, 3D point cloud reconstruction, registration, and classification as well as texture projection and completion.
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6+ years' experience in engineering data pipelines using big data technologies (Spark, Flink etc. Make smart engineering and product decisions based on data analysis and collaboration.
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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.
$283,800 a yearFull-timeRemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Architect, build, and support the operation of Cloud and On-Premises enterprise data infrastructure and tools to support critical operational processes, analytical models, and machine learning applications.
$153,600 - $341,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (, AWS, Google Data Analytics, Microsoft Azure) Information for applicants with a need for accommodation: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
$119,025 - $198,375 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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In this role, you’ll be embedded in the Risk & Fraud organization and work closely with machine learning, product management as well as other cross-functional partners to drive strategy using a variety of data science techniques and own north star metric monitoring.
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Data Processing and Feature Engineering: Develop pipelines and tools for data processing, feature engineering, and preprocessing to support machine learning model development.
$150,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Incorporate subjective data from human perception experiments into machine learning models. Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
$44 an hourFull-timeExpandApply NowActive JobUpdated Today
machine learning data mining engineering jobs Title: engineer data Company: Amazon Web Services Aws in San Francisco, CA
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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.
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The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).
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Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
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If you’re like most of us, you’d love to be wealthier. Having more money would alleviate stress. It would make it easier to pay your bills and buy nicer things. Maybe it’d allow you to spend more time with your kids and go on more vacations. You’re not alone if you wish you could somehow earn a more significant income.