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Develop implement and optimize NLP solutions utilizing LLMs tailored for financial data and equities.
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Manage and deploy Machine Computing Platforms (MCP) to support scalable AI workloads.
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Collaborate with data scientists and engineers to integrate AI models into production environments.
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Maintain and enhance AI infrastructure on AWS cloud services and Linux-based servers.
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Apply traditional machine learning techniques on structured large datasets to complement NLP efforts.
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Troubleshoot and resolve software/hardware issues related to AI systems and server environments.
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Stay updated with the latest advancements in NLP LLMs and machine learning best practices.
Requirements:
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Deep knowledge of Natural Language Processing including expertise with Large Language Models (e.g. GPT BERT similar architectures).
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Hands-on experience in implementing fine-tuning and deploying LLMs in production.
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Proven experience managing and operating MCP or similar machine learning platforms.
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Strong proficiency with AWS cloud services (EC2 S3 Lambda etc.) and experience working with Linux server environments.
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Knowledge of traditional machine learning models applied on structured big data is a plus.
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Prior experience in equities or financial data analysis is highly preferred.
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Programming proficiency in Python and familiarity with relevant AI frameworks (e.g. TensorFlow PyTorch Hugging Face).
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Strong problem-solving skills and ability to work in a fast-paced collaborative environment.
Preferred but not required:
Develop implement and optimize NLP solutions utilizing LLMs tailored for financial data and equities. Manage and deploy Machine Computing Platforms (MCP) to support scalable AI workloads. Collaborate with data scientists and engineers to integrate AI models into production environments. Main...
-
Develop implement and optimize NLP solutions utilizing LLMs tailored for financial data and equities.
-
Manage and deploy Machine Computing Platforms (MCP) to support scalable AI workloads.
-
Collaborate with data scientists and engineers to integrate AI models into production environments.
-
Maintain and enhance AI infrastructure on AWS cloud services and Linux-based servers.
-
Apply traditional machine learning techniques on structured large datasets to complement NLP efforts.
-
Troubleshoot and resolve software/hardware issues related to AI systems and server environments.
-
Stay updated with the latest advancements in NLP LLMs and machine learning best practices.
Requirements:
-
Deep knowledge of Natural Language Processing including expertise with Large Language Models (e.g. GPT BERT similar architectures).
-
Hands-on experience in implementing fine-tuning and deploying LLMs in production.
-
Proven experience managing and operating MCP or similar machine learning platforms.
-
Strong proficiency with AWS cloud services (EC2 S3 Lambda etc.) and experience working with Linux server environments.
-
Knowledge of traditional machine learning models applied on structured big data is a plus.
-
Prior experience in equities or financial data analysis is highly preferred.
-
Programming proficiency in Python and familiarity with relevant AI frameworks (e.g. TensorFlow PyTorch Hugging Face).
-
Strong problem-solving skills and ability to work in a fast-paced collaborative environment.
Preferred but not required:
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