IN_Senior Associate_Gen AI_Data and Analytics_Advisory_Bangalore

Responsibilities

• 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 Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert
• Proficient in Python, SQL, Javascript

Mandatory skill sets