Long Description

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.

· Ability to work with APIs to integrate AI models with external data sources and systems.

· Strong problem-solving skills and the ability to work independently and as part of a team.

· Excellent communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders.

Long Description

Preferred Qualifications

· Experience with MLOps practices, including model versioning, CI/CD for ML, and pipeline automation.

· Familiarity with Google Cloud Storage, BigQuery, and other GCP services.

· Knowledge of vector databases and experience working with semantic search technologies.

· Exposure to data labeling and active learning techniques for improving model performance.

· Experience in developing scalable AI/ML solutions for NLP tasks such as entity extraction, text summarization, and question answering

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