AI Technology Ecosystem Architect

IBM

Quick summary

Work type: On-site
Location: Seattle, WA
Posted: 10 days ago

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Similar $202k

$153k most similar roles pay here $251k

This listing doesn't post a salary. Most similar roles pay $162,375–$241,600.

Based on 240 similar postings.

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

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Listed pay typically runs $1,000,000–$1,000,000 across 8 roles with salary data.

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At a glance

TL;DR · AI Technology Ecosystem Architect

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As an AI Technology Ecosystem Architect at a leading tech company in Seattle, you will join a dynamic team of experts focused on advancing the integration and application of artificial intelligence across various domains. Your primary responsibilities include designing and implementing scalable solutions for foundation models and large language models (LLMs), ensuring seamless interaction between these technologies and existing systems. You will work closely with cross-functional teams to identify opportunities for innovation, optimize performance, and enhance user experiences. Proficiency in Python, TensorFlow, or PyTorch is essential, along with expertise in cloud platforms like AWS or Azure. A deep understanding of machine learning principles and hands-on experience with natural language processing (NLP) will be crucial as you tackle complex challenges related to AI scalability and interoperability within a rapidly evolving technological landscape.

Skills

Python TensorFlow PyTorch Kubernetes Docker AWS Azure GCP CI/CD Git PostgreSQL MongoDB Redis GraphQL REST Swagger Kafka Prometheus Grafana

What you'll do

Design and implement scalable AI solutions using foundation models and large language models.
Integrate advanced AI technologies into existing enterprise systems to enhance functionality.
Develop innovative use cases for AI technology to drive business growth and efficiency.
Stay updated with the latest advancements in AI and machine learning techniques.
Create detailed technical documentation and guidelines for AI implementation projects.

What we're looking for

Extensive experience in designing and implementing AI technology ecosystems.
Proficiency in foundation models and large language models (LLMs).
Strong background in cloud computing platforms like AWS, Azure, or GCP.
Expertise in machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Experience with data engineering tools for big data processing and analytics.
Solid understanding of cybersecurity principles to protect AI systems.
Excellent communication skills for collaborating with cross-functional teams.

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