Support Architect - Entry level

Remote, USA Full-time Posted 21-11-2024 08:14

Introduction
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Your Role and Responsibilities

ROLE:

We are seeking a talented and experienced Full-Stack Software Engineer to join our dynamic and innovative technology team. As a Full-Stack Software Engineer, you will be responsible for designing, developing, and maintaining both the front-end and back-end components of our web applications. You will work closely with our product and design teams to create user-friendly interfaces and efficient back-end systems. Some AI Engineering responsibilities would involve knowledge in Machine Learning models and Large Language Models.

RESPONSIBILITIES:

Design, code, test, and manage various applications for our clients. Collaborate with the product and design teams to establish best products. Write clean, scalable, and maintainable code. Troubleshoot and debug applications. Conduct thorough testing to ensure high-quality software. Stay up to date with new technologies and industry trends. Evaluating machine learning processes, collecting and analyzing large amounts of data. Programming AI software to utilize large amounts of data. Developing and deploying AI algorithms.

Required Technical and Professional Expertise
In-depth knowledge of front-end technologies (e.g., HTML, CSS, JavaScript, React, Angular, Vue.js) Experience with back-end technologies (e.g., Node.js, Python, Ruby, PHP, Java) Knowledge of database management systems (e.g., MySQL, PostgreSQL, MongoDB).

Preferred Technical and Professional Expertise
Experience in implementing LLMs using vector bases and Retrieval-Augmented Generation (RAG), as well as tuning models. Using GPTs, Llama, or any other LLM.

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