Senior AI/ML Architect for Scalable GenAI & MLOps

Good co India; United States; Remote; USD 140,000 - 230,000; Full time

Job summary

Good co India seeks an experienced AI/ML Architect to define scalable, secure architectures and lead end-to-end ML systems. You will drive data ingestion, feature engineering, model training, evaluation, and deployment while optimizing performance and cost.

Responsibilities include overseeing generative AI applications, LLMs, RAG, vector databases, and AI agents, with a strong focus on governance, privacy, and reliability.

Qualifications

• Bachelor’s or higher in CS/AI/IT or related field.
• 5–10 years in software/data science/AI solution roles with architecture leadership.
• Strong Python programming and experience with ML frameworks.
• Experience deploying enterprise AI solutions at scale.

Responsibilities

• Define and lead scalable, secure AI/ML architectures aligned with business goals.
• Design end-to-end ML systems: ingestion, preprocessing, training, deployment, monitoring.
• Develop AI solutions using ML, DL, NLP, and CV tech.
• Architect generative AI apps with LLMs, RAG, vector stores, and AI agents.
• Establish MLOps/LLMOps for automation, versioning, monitoring, lifecycle management.
• Design cloud-native AI solutions on AWS/Azure/GCP and ensure enterprise-grade quality.
• Collaborate with data scientists, engineers, and stakeholders to translate problems to AI solutions.

Skills

AI/ML architecture

MLOps/LLMOps

Python

SQL

TensorFlow

PyTorch

LangChain

RAG

Vector databases

Cloud platforms

Education

Bachelor's degree in CS/AI/IT

Master's degree in AI/ML or related field

Tools

AWS

Azure

GCP

Docker

Kubernetes

MLflow

Job description

Good co India seeks an experienced AI/ML Architect to define scalable, secure architectures and lead end-to-end ML systems. You will drive data ingestion, feature engineering, model training, evaluation, and deployment while optimizing performance and cost.

Responsibilities include overseeing generative AI applications, LLMs, RAG, vector databases, and AI agents, with a strong focus on governance, privacy, and reliability.