Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4352051553&f_AL=true&f_TPR=r86400&f_WT=2&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER&start=75 Job Description: Artificial Intelligence Consultant The HIRD- USA · United States (Remote) Easy Apply Save Save Artificial Intelligence Consultant at The HIRD- USA Show more options Your profile is missing required qualifications Show match details Help me update my profile BETA Is this information helpful? Get personalized tips to stand out to hirers Find jobs where you’re a top applicant and tailor your resume with the help of AI. Try Premium for PKR0 Meet the hiring team David Taylor David Taylor 3rd Talent Acquisition Specialist at The HIRD Job poster Message About the job  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.