AI Platform Architect
AI Platform Architect
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Job Description
Our Company
Changing the world through digital experiences is what Adobes all about. We give everyonefrom emerging artists to global brandseverything they need to design and deliver exceptional digital experiences! Were passionate about empowering people to create beautiful and powerful images videos and apps and transform how companies interact with customers across every screen.
Were on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization and we know the next big idea could be yours!
Job Description
The candidate should have proven expertise in building scalable platforms that are customer facing and have expertise in evangelizing the platform with customers and with internal stakeholders Expert level knowledge of Cloud Computing including aspects of VPC Network Design Shared Responsibility Matrix Cloud databases No SQL Databases Data Pipelines on the cloud VM and VM orchestration Serverless frameworks. This should be across all 3 major cloud providers (AWS Azure GCP) preferably at least in 2 of the 3 Public Clouds Expert level knowledge in Data Ingestion paradigms & use of different types of databases like OLTP OLAP for specific purposes Hands-on experience with Apache Spark Apache Flink Kafka Kinesis Pub/Sub Databricks Apache Airflow Apache Iceberg and Presto. Expertise in designing ML Pipelines for experiment management model management feature management model retraining A/B testing of models and design of APIs for model inferencing at scale. Proven expertise with Kube Flow SageMaker/Vertex AI/Azure AI. SME in LLM Serving paradigms deep knowledge of GPU architectures distributed training and serving of large language models. Expertise in Model and Data parallel training expertise with frameworks like DeepSpeed and service frameworks like vLLM etc. Proven expertise in Model finetuning and model optimization techniques to achieve better latencies better accuracies in results. Be an expert in reducing training and resource requirements of finetuning of LLM and LVM models. Have a wide knowledge of different LLM models and have an opinion on aspects of applicability of each model based the usecases. Proven expertise of having worked on specific customer usecases and having seen delivery of a solution end to end from engineering to production. Proven expertise in DevOps and LLMOps knowledge of Kubernetes Docker and container orchestration and deep knowledge of LLM Orchestration frameworks like Flowise Langflow 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
Dev Ops: Kubernetes Docker FluentD Kibana Grafana Prometheus
Databases/Datawarehouse: DynamoDB Cosmos MongoDB RDS MySQL PostGreSQL Aurora Spanner Google BigQuery.
Cloud Expertise: AWS/Azure/GCP
Cloud Certifications: AWS Professional Solution Architect AWS Machine Learning Specialty Azure Solutions Architect Expert
Proficient in Python SQL Javascript
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Employment Type
Full-Time
