AI Platform Engineer

We're 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!

Key Responsibilities

·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