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Our next-generation platform, which combines threat intelligence with machine learning, enables financial institutions and governments to detect cryptocurrency fraud and financial crime on an unprecedented scale.
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OSARO is a San Francisco-based startup company building machine learning software for industrial automation, to power robots in logistics and material handling centers. You will collaborate with Operations, Software, and Machine Learning teams to research, design, integrate, test and deploy new robotic hardware including: robot cell designs, end effectors, cameras, lighting, HW control devices (PLCs, I/O couplers, sensors, etc), pneumatics, actuators, custom mechanisms.
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Contribute to machine learning and large language model (LLM) pipelines and APIs, including OpenAI (GPT-3.5 and GPT-4), Azure (OpenAI), Anthropic (Claude), and others. Provision of anything you need to be successful - learning tools, hardware, office equipment, software.
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Overview of the Software Engineer - Machine Learning roleThe Williams-Sonoma, Inc. Technology organization seeks a talented Software Engineer - Machine Learning to assist with developing strategies, roadmaps, frameworks and solutions as a key member of our AI & Machine Learning team.
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This engineer works within a team developing StubHub’s next-generation Customer Support platform, integrating Siebel, with our telephony, eCommerce and Business Process Management portals.
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Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. The candidate will join a multi-disciplinary team of scientists and engineers and work on a full stack of developing cutting edge Computer Vision (CV) and Machine Learning (ML) methods based on data from a variety of sensors.
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Perplexity is seeking an experienced Software Engineer to design and implement next-generation billing systems. Collaborate with peers across engineering, customer success, finance, and data science teams to ensure precise measurement and reporting.
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You will build and apply machine learning techniques to biochemical / biophysical datasets and aid in new hypothesis generation with experimental collaborators. 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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Work cross-functionally with product, platform, security, and data engineering teams to unlock new machine learning applications. This team builds and integrates ML solutions for evaluating customer cash flow risk including risk of default on credit obligations, risk of fraud & abuse of loans and other situations where Cash App advances funds or provides liquidity to customers.
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Coactive was founded by experts who shaped the fields of high-performance deep learning and data-centric AI. We have the scars from building and working with the first generation of modern machine learning systems at Google, Meta, Pinterest, eBay, Lyft, and other leading organizations.
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Build from scratch a suite of data science and machine learning solutions that will make up the core of Square’s next generation attribution system. We are looking for a senior Machine Learning Engineer with deep expertise in attribution space (just like you.
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Lead Machine Learning Engineer. 3+ years experience developing ETL workflows as a data analytics engineer, data engineer, or data analyst. Uses software development best practices with a focus on testing, reliability and maintainability.
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Experience as a laboratory technician Experience with PCR, PCR optimization Experience with performing next-generation sequencing, including whole genome and / or targeted Amplicon sequencing Experience with culturing bacteriophage Advanced knowledge of Database software, statistical software (e.g. STATA, R) Computer programming (e.g. Python, C.
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At Candid Health, we’re searching for our first Data Engineer to design, build, and support our next generation of data infrastructure. We’re rethinking medical billing from the ground up, building software backed by best-in-class data science (and, soon, a dash of machine learning) to automate much of this complexity so healthcare providers can get paid dramatically more easily and inexpensively.
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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.
$177,000 - $245,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated Today
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