AI/ML Developer - Large Language Models (LLMs)

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AI Summary

We are seeking a talented AI/ML Developer with experience in developing, deploying, and fine-tuning machine learning models using Google Cloud Platform (GCP) tools like Vertex AI. The ideal candidate has a strong foundation in machine learning and AI technologies, along with hands-on experience with cloud-based AI/ML platforms.

Key Highlights
Develop and deploy Large Language Models (LLMs) on Vertex AI and AWS Bedrock
Build and maintain RAG pipelines for data-driven decision-making
Collaborate with cross-functional teams to build scalable AI solutions
Technical Skills Required
Python Google Cloud Platform (GCP) Vertex AI AWS Bedrock TensorFlow PyTorch Hugging Face Transformers scikit-learn Apache Beam Dataflow BigQuery
Benefits & Perks
100% Remote
Competitive pay
Day one benefits
Opportunities for career advancement

Job Description


 Location: Remote

 Reports To: AI Product Director

 Employment Type: Full Time


Our client is seeking individuals who combine excellent customer service and problem-solving

skills with the ability to function effectively both as part of a team or on an individual basis

to bring their talent to our team.

Our client is a leading global IT Solutions and Services company with over 200,000 dedicated

employees serving clients across more than 66 countries.

They offer a strong compensation package that includes competitive pay and day one benefits.

They also offer many opportunities for career advancement within an engaging and

exciting culture.


100% Remote

USC and Green Card only

No relocation


Overview:

We are looking for a talented AI/ML Developer with experience in developing,

deploying, and fine-tuning machine learning models using Google Cloud Platform

(GCP) tools like Vertex AI. This role involves working with state-of-the-art Large

Language Models (LLMs), building and maintaining RAG (Retrieval-Augmented

Generation) pipelines, and handling complex data preprocessing tasks. The ideal

candidate has a strong foundation in machine learning and AI technologies, along with

hands-on experience with cloud-based AI/ML platforms such as Vertex AI and AWS

Bedrock. You will collaborate with cross-functional teams to build scalable, high-

performance AI solutions that meet business requirements.


Key Responsibilities:

 Develop, deploy, and fine-tune Large Language Models (LLMs) on platforms

like Vertex AI and AWS Bedrock.

 Build, optimize, and maintain RAG (Retrieval-Augmented Generation)

pipelines to support data-driven decision-making and enhance model accuracy.

 Perform complex data preprocessing, including cleaning, feature engineering,

and transformation, to prepare data for ML pipelines.

 Design and implement scalable machine learning models for a variety of

business applications, focusing on NLP and generative AI.

 Utilize Vertex AI, AWS Bedrock, or similar cloud-based tools to manage the

entire ML lifecycle, from model training to deployment.

 Collaborate with data engineers, data scientists, and software engineers to

integrate AI/ML models into production systems.

 Conduct model evaluation, A/B testing, and continuous improvement through

hyperparameter tuning and retraining.

 Monitor and manage deployed models to ensure their performance, scalability,

and reliability over time.

 Document technical processes, model architecture, and key decisions for

ongoing maintenance and knowledge sharing.


Qualifications:

 Bachelor’s or Master’s degree in Computer Science, Data Science, Machine

Learning, or a related field.

 3+ years of experience in AI/ML development, with hands-on experience in

model training, deployment, and monitoring.

 Proficiency with GCP tools such as Vertex AI and familiarity with similar

platforms like AWS Bedrock for model deployment and management.

 Experience in developing, fine-tuning, and deploying Large Language Models

(LLMs).

 Strong understanding of NLP, deep learning frameworks (such as TensorFlow

or PyTorch), and generative AI techniques.

 Solid grasp of data preprocessing techniques for structured and unstructured

data.

 Proficiency in programming languages such as Python and experience with ML

libraries like scikit-learn, Hugging Face Transformers, and TensorFlow.

Skills

 Experience with RAG pipelines, including building custom retrieval mechanisms

and integrating with LLMs.

 Knowledge of model evaluation techniques and experience in A/B testing for

model validation.

 Familiarity with cloud computing concepts and experience in deploying AI/ML

models in a cloud environment.

 Hands-on experience with big data processing tools, such as Apache Beam,

Dataflow, or BigQuery.


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