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Experience with machine learning tools such as mlFlow, Databricks AI/ML, Azure ML, AWS sagemaker, etc. Hands-on experience to design and build solution powered by DBT models and integrate with databricks.
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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 design.
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Job Description We have multiple openings for Computational Bioengineers who will conduct research leading to our next-generation, machine learning-driven computational pipeline for protein design and optimizing protein-protein interactions as part of the Center for Predictive Bioresilience (CPB.
$245,544 a yearFull-timeExpandApply NowActive JobUpdated Today - 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.
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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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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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8-10 years of experience working as a Software Engineer, DevOps Engineer, MLOps Engineer, or Machine Learning Engineer within a production ecosystem. We are seeking a dedicated Machine Learning Engineer with a passion for data science, to lead and manage our critical Machine Learning and Artificial Intelligence Platform.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 3+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service. develop, developer, devops, perl, programming, sde, software engineer.
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Job Description :We are looking for a seasoned Machine Learning Engineer specialized in Large Language Models (LLMs) to drive the development and deployment of cutting-edge AI solutions.
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Join Apple's Applied Machine Learning Team, as a Senior Software Engineer, to enable GenAI across our Applications & Platforms. Build LLM Applications using open source LLM App Frameworks, AWS BedRock/GCP Vertex AI.
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LLM-Optimized MLOps Infrastructure: Design and implement MLOps infrastructure on AWS tailored for LLMs, leveraging services like SageMaker, EC2 (with GPU instances), S3, ECS/EKS, Lambda, and more.
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Deep expertise in one or more relevant fields (e.g., antibody biology, biophysics, biotherapeutic design, machine learning). Apply and advance artificial intelligence and machine learning (AI/ML) approaches, particularly generative AI models, across stages of large molecule workflows, including molecular property predictions, AI-guided candidate selection and engineering.
$214,280 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.
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Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with machine learning concepts and frameworks is a plus. NOTE: THIS POSITION IS TO JOIN AS W2 ONLY. Data Engineer with Databricks Location: Remote Duration: 6+ Months Daily Responsibilities: Design, develop, test, deploy, maintain, and improve software applications and services.
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Utilize expertise in computational biology, machine learning, and bioinformatics to develop and optimize algorithms and models for the analysis of high-dimensional biological data. A Ph. D. or equivalent in computational biology, bioinformatics, machine learning, or a related field is preferred.
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