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By joining us as a Principal Machine Learning Engineer, Infrastructure (LLM), you will work on state-of-the-art systems, contribute to cutting-edge research, develop innovative algorithms, and play an essential part in Prescient Design's success.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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We are looking for a passionate Software Engineer, Big-Data Engineer, Machine-Learning Engineer, Full-stack Engineer, or UI/UX Engineer, who can contribute and make a difference in any of the different components of our Knowledge Graph Platform.
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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, and Machine Learning engineers for full-time positions with clients.
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We’re looking for a passionate Applied Machine Learning expert to join our team. Machine learning background in Python; experience with PyTorch, TensorFlow, or similar frameworks and familiarity with Natural Language Processing (LLM, Entity Recognition, Entity Resolution, Classification), Graph-based Models, and Computer Vision.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. You'll make valuable contributions from day one by continuously learning, engaging in diverse sets of experiences, and building close-knit relationships across the company.
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Julia, MATLAB, Scala, LISP, Prolog, and JavaScript for various AI/ML applications, including data analysis, high-performance computing, enterprise-level applications, and web-based MLExperience with AI and machine learning frameworks (, TensorFlow, PyTorch, Scikit-learn.
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Demonstrated track research record in the fields of statistics, machine learning, computational biology, data science or related field (computer science, physics, biostatistics, bioinformatics.
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Architect and implement big data processing solutions using Databricks, leveraging Apache Spark for data transformation, ETL processes, and machine learning workflows. Our success lies in creating a fun, transparent, non-hierarchical, diverse work culture that focuses on continuous learning and work-life balance.
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with a strong background in PC-DMIS to join our team.
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Experience leading teams in data analytics and data visualization, including selecting and applying the appropriate analytical techniques for statistical analysis, predictive modeling, simulation, and machine learning.
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MLOps and Deployment: Hands-on experience in deploying machine learning models using CI/CD pipelines, containers (Docker, Kubernetes), and APIs for serving LLM/NLP models at scale. Cloud Platforms: Experience with cloud-based machine learning and AI platforms such as AWS (SageMaker, Lambda) and Snowflake with a focus on GenAI model training, deployment, and monitoring.
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Using our proprietary platform combining spatial biology, pooled screening, in silico protein engineering, and machine learning, we can obtain both depth and breadth when screening cell therapy candidates – speed without compromising on in vivo accuracy.
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Provide technical vision, drive strategy around solutions, solve complex problems, and act as the technical owner across strategic efforts involving the UI/UX platform, Cloud, streaming, machine learning, and more.
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This is an ideal role for someone who thrives in ambiguity and has a consistent track record of contributing to the product strategy and roadmap for a complex machine learning problem space.
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machine learning jobs Title: scientist applied Company: Kadence in New York, IN, Pennsylvania
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