Remove Algorithm Remove Data Preparation Remove System Architecture
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Ask HN: Who is hiring? (July 2025)

Hacker News

If you want to work on operating production critical databases in the cloud on k8s + write data-driven algorithms for autoscaling, consider applying! Fun engineering challenges: These include complex distributed systems, low-latency algorithms & infrastructure, and modeling sales calls with large language models.

Python 90
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Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator

AWS Machine Learning Blog

Such a pipeline encompasses the stages involved in building, testing, tuning, and deploying ML models, including but not limited to data preparation, feature engineering, model training, evaluation, deployment, and monitoring.

professionals

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Embedded AI Integration with MATLAB and Simulink

Pickl AI

Role of MATLAB and Simulink in Embedded AI MATLAB and Simulink are powerful tools that facilitate the development of embedded AI systems. They provide a comprehensive environment for designing algorithms, simulating their performance, and generating code for deployment on various hardware platforms.

AI 52
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A Guide to LLMOps: Large Language Model Operations

Heartbeat

This is brought on by various developments, such as the availability of data, the creation of more potent computer resources, and the development of machine learning algorithms. Deployment : The adapted LLM is integrated into this stage's planned application or system architecture.