Role Title: AI Platform Engineer ( Only immediate joiner need to apply)

CTC- UP to 35LPA

Location: Bangalore (In Person in office when required)

Part of the GenAI COE Team

Key Responsibilities

- Platform Development and Evangelism:

- Build scalable AI platforms that are customer-facing.

- Evangelize the platform with customers and internal stakeholders.

- Ensure platform scalability, reliability, and performance to meet business

needs.

Machine Learning Pipeline Design:

- Design ML pipelines for experiment management, model management, feature

management, and model retraining.

- Implement A/B testing of models.

- Design APIs for model inferencing at scale.

- Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI.

LLM Serving and GPU Architecture:

- Serve as an SME in LLM serving paradigms.

- Possess deep knowledge of GPU architectures.

- Expertise in distributed training and serving of large language models.

- Proficient in model and data parallel training using frameworks like DeepSpeed

and service frameworks like vLLM.

Model Fine-Tuning and Optimization:

- Demonstrate proven expertise in model fine-tuning and optimization

techniques.

- Achieve better latencies and accuracies in model results.

- Reduce training and resource requirements for fine-tuning LLM and LVM models.

LLM Models and Use Cases:

- Have extensive knowledge of different LLM models.

- Provide insights on the applicability of each model based on use cases.

- Proven experience in delivering end-to-end solutions from engineering to

production for specific customer use cases.

DevOps and LLMOps Proficiency:

- Proven expertise in DevOps and LLMOps practices.- Knowledgeable in Kubernetes, Docker, and container orchestration.

- Deep understanding of LLM orchestration frameworks like Flowise, Langflow,

and Langgraph.

Skill Matrix

LLM: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama

LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker,

AWS Bedrock, Vertex AI, Azure AI

Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL,

PostGreSQL, Aurora, Spanner, Google BigQuery.

Cloud Knowledge: AWS/Azure/GCP

Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus

Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine

Learning Specialty, Azure Solutions Architect Expert

Proficient in Python, SQL, Javascript