AI Engineer I

adobe

Bangalore 7 Years Exp Posted 256d ago

Job Description

Experience: 7-10 years

 

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

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