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AI Platform Engineer @ Adobe

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 AI Platform Engineer

Job Description

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

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Science & Machine Learning - Other
Employement Type: Full time

Contact Details:

Company: Adobe
Location(s): Bengaluru

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Keyskills:   GCP Postgresql MySQL Machine learning Javascript Adobe Cosmos Data warehousing SQL Python

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Adobe

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