AIML Architect

Acme Services Private Limited; Bengaluru; Sur place; INR 2 500 000 - 5 000 000; Plein temps

Résumé du poste

Acme Services Private Limited in Bengaluru seeks a senior AI/ML Architect to define end-to-end architectures for GenAI, LLM serving, and enterprise AI patterns. You will design scalable solutions across AWS, Azure, and GCP, lead MLOps practices, and guide engineering teams in implementing secure, cost-effective AI platforms.

Responsibilities include framing HLD/LLD, containerized workloads with Docker/Kubernetes, and integrating vector databases, embeddings, and retrieval-augmented systems while

Qualifications

• Proven experience designing AI/ML architectures for large-scale enterprise use cases.

Responsabilités

• Define end-to-end AI/ML solution architectures for enterprise use cases.
• Design scalable architectures for LLM, RAG, Agentic AI, and ML solutions.
• Create HLD and LLD for AI platforms and applications.
• Architect microservices-based AI/ML solutions using Python and FastAPI.
• Define architecture strategies for model serving, deployment, and optimization.

Connaissances

AI Architecture

GenAI

MLOps

Python

LLM

LangChain

HuggingFace

Docker

Kubernetes

VectorDB

Cloud Platforms

Outils

Docker

Kubernetes

FastAPI

Terraform

CloudFormation

LangChain

HuggingFace

VectorDB

Description du poste

Job Description:

• Define end-to-end AI/ML and GenAI solution architectures for enterprise use cases.

• Design scalable and secure architectures for LLM, RAG, Agentic AI, and Machine Learning solutions.

• Create High-Level Design (HLD) and Low-Level Design (LLD) for AI/ML platforms and applications.

• Architect microservices-based AI/ML solutions using Python and FastAPI.

• Design RAG architectures using vector databases, embeddings, semantic search, and knowledge retrieval.

• Architect LLM-based applications using frameworks such as Hugging Face Transformers and LangChain.

• Define architecture and technology strategies for LLM serving, model deployment, inference, and optimization using technologies such as vLLM and FastAPI.

• Design and implement MLOps architecture covering model deployment, monitoring, retraining, versioning, and lifecycle management.

• Architect containerized AI/ML workloads using Docker and Kubernetes (K8s).

• Design CI/CD and DevOps architecture using GitHub Actions, Jenkins, Helm, and Infrastructure as Code tools such as Terraform or CloudFormation.

• Design AI/ML solutions across AWS, Azure, and GCP, considering scalability, reliability, cost, and security.

• Define architecture for model quantization, knowledge distillation, fine-tuning, evaluation, and performance optimization.

• Establish best practices for AI/ML security, data privacy, model governance, and responsible AI.

• Evaluate emerging AI/ML technologies and recommend appropriate frameworks, tools, and platforms.

• Provide technical leadership and architectural guidance to AI/ML engineering teams.

• Collaborate with business, data, engineering, cloud, and security stakeholders to translate requirements into scalable AI/ML architectures.

• Review technical designs, conduct architecture reviews, and ensure adherence to enterprise standards.

• Lead the architecture and implementation of AI/ML use cases such as chatbots, recommendation systems, intelligent automation, translation, and enterprise GenAI applications.