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We're looking for someone who has a passion for building scalable machine learning and MLOps platforms using technologies such as Python, Databricks, Spark, AWS, Airflow, Terraform, etc.
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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. Develop new features for a large and complex Vue.js application, and corresponding backend APIs in Python microservices.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture designAbility to align AI/ML initiatives with broader business goals and outcomes, understanding how AI can drive value and competitive advantage.
$174,000 - $218,000 a yearFull-timeExpandApply NowActive JobUpdated 20 days ago - UpvoteDownvoteShare Job
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Strong background in platforms and tools such as OpenAI, Azure Semantic Kernel, AWS Bedrock, and other machine learning technologies, with a focus on Generative AI and open-source AI frameworks.
$174,000 - $218,000 a yearFull-timeExpandApply NowActive JobUpdated 20 days ago - UpvoteDownvoteShare Job
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Bachelor's degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines and 5 or more years experience in predictive analytics or equivalent.
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Preferred Qualifications: 2+ years of experience as a developer, data scientist or machine learning engineer in addition to 2+ years of experience in a TPM role Prior development or management experience on a Machine Learning Platform in a large tech company Hands-on experience with cloud technologies and service oriented architectures Track record of using data analytics for improving SW operations and organizational efficiency Advanced degree in an analytical field.
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As a key contributor to our Machine learning efforts across Snap, you will take ownership of technology development synergy and operations across a team of experienced and talented researchers and engineers.
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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. Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
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Stay up to date on state-of-the-art machine learning methodologies and their applications in cell engineering and drug discovery. We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines.
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Adobe Firefly Applied Science & Machine Learning (ASML) group is looking for an Engineering Manager working on generative AI models for image synthesis to help us build the next generation of creative tools.
$148,600 - $298,800 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Explore new machine learning and artificial intelligence approaches for automated object detection, feature extraction/target state estimation, multi-source data fusion, and much more.
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Evaluate commercial and open-source techniques in Machine Learning, Data Mining, NLP, and Analytics. Master's degree in Computer Science, Statistics, or Mathematics required with emphasis on data mining, NLP, or machine learning.
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Familiarity with cloud platforms that offer specific support for deploying and scaling generative models, such as Google s Vertex AI, Azure s AI tools, and AWS s Machine Learning services.
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As a data scientist, you will be tackling time-series based machine learning problems to help build the next generation of algorithms that will provide early prediction for these patients and their doctors.
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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications within The Friedkin Group of companies. Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP.
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