AI ML Vertex

Job Title: AI/ML Engineer – Vertex AI & Generative AI

Experience: 4-10 Years

Location: Hyderabad/ Gurgaon / Bangalore

Employment Type: Full-Time

Job Summary

We are looking for a highly skilled AI/ML Engineer with expertise in Google Vertex AI to design, develop, deploy, and optimize machine learning and Generative AI solutions on Google Cloud Platform (GCP). The ideal candidate will have strong experience in ML model development, MLOps, LLMs, Vertex AI services, and cloud-native AI deployments.

Key Responsibilities

• Design, develop, train, and deploy machine learning models using Vertex AI.
• Build and maintain end-to-end ML pipelines for data preparation, training, evaluation, deployment, and monitoring.
• Implement MLOps best practices for model lifecycle management and automation.
• Develop and deploy Generative AI solutions leveraging Vertex AI and Gemini models.
• Fine-tune, evaluate, and optimize machine learning and foundation models.
• Build RAG (Retrieval-Augmented Generation) applications using Vertex AI, Vector Search, and LLMs.
• Collaborate with Data Engineers, Data Scientists, and business stakeholders to deliver AI-driven solutions.
• Monitor deployed models for performance, drift, and reliability.
• Ensure scalability, security, governance, and responsible AI practices.
• Optimize cloud infrastructure and AI workloads for cost and performance.

Required Technical Skills

Machine Learning & AI

• Strong understanding of:
• Supervised and Unsupervised Learning
• Deep Learning
• NLP
• Computer Vision
• Recommendation Systems
• Experience with model training, evaluation, and deployment.

Programming

• Python (Advanced)
• SQL
• Experience with ML libraries:
• TensorFlow
• PyTorch
• Scikit-learn
• Pandas
• NumPy

Vertex AI

• Vertex AI Workbench
• Vertex AI Pipelines
• Vertex AI Model Registry
• Vertex AI Endpoints
• Vertex AI Feature Store
• Vertex AI Model Monitoring
• Vertex AI Vector Search
• Vertex AI Agent Builder
• Prompt Engineering
• Gemini Models

Generative AI

• Large Language Models (LLMs)
• Prompt Engineering
• RAG Architecture
• Embeddings and Vector Databases
• Model Fine-Tuning
• Agentic AI Workflows

Google Cloud Platform (GCP)

• BigQuery
• Cloud Storage
• Dataflow
• Pub/Sub
• Cloud Functions
• Cloud Run
• GKE (Google Kubernetes Engine)

MLOps & DevOps

• Docker
• Kubernetes
• Git/GitHub
• CI/CD Pipelines
• Terraform
• MLflow (Optional)

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• Experience with enterprise AI/ML deployments on cloud platforms.
• Google Cloud Certifications:
• Professional Machine Learning Engineer
• Professional Cloud Architect
• Experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar AI frameworks.