& Summary:

AI Engineer

Level: Senior Associate

Location: Noida,Bangalore

Skill: Gen AI,LLM, Huggingface, python,pytorch/tensor flow/keras, Langchain, Langgraph, Docker,

Kunernetes

Job Position Title

Responsibilities

AI Engineer

ML Pipeline Design

Design ML pipelines for experiment management, model management,

feature management, and model retraining.

Design APIs for model inferencing at scale.

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

LLM Serving and GPU Architecture:

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.

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 Skilled Solution Architect, AWS

Machine Learning Specialty, Azure Solutions Architect Expert

Proficient in Python, SQL, Javascript

Mandatory skill sets

Gen AI,LLM, Huggingface, python,pytorch/tensor flow/keras, Langchain,

Langgraph, Docker, Kunernetes

Years of experience required

Education qualification

5-8 years

B.Tech/MCA/BCA/M.tech

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