Overview

We are seeking an experienced ML Architect to build and scale customer data science workloads, applying best-in-class MLOps practices to productionize solutions across a variety of domains. The role involves developing cutting-edge LLM solutions including RAG architectures on enterprise knowledge repositories, natural language querying of structured data, and content generation. The ML Architect will serve as a trusted advisor to data teams on architecture, tooling, and best practices, while also providing technical mentorship to the broader ML Subject Matter Expert community. The ideal candidate brings deep hands-on data science expertise, strong communication skills, and a passion for driving business value through machine learning.

Key Responsibilities

• Build and scale customer data science workloads and apply best MLOps practices to productionize these workloads across a variety of domains
• Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repositories
• Implement natural language querying of structured data and content generation solutions
• Advise data teams on data science architecture, tooling, and best practices
• Provide technical mentorship to the larger ML Subject Matter Expert community
• Communicate and teach technical concepts to both non-technical and technical audiences
• Meet expectations for technical training and role-specific outcomes within 3 months of hire

Required Skills

• 6-10 years of hands-on industry data science experience
• Pandas
• MLflow
• Scikit-learn
• Gensim
• NLTK
• TensorFlow
• PyTorch
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Drift monitoring for ML deployments
• Vector databases
• Fine-tuning LLMs
• Deploying LLMs
• HuggingFace
• LangChain
• OpenAI
• Graduate degree in Computer Science, Engineering, Statistics, Operations Research or equivalent practical experience
• Experience communicating and teaching technical concepts to non-technical and technical audiences
• Passion for collaboration, life-long learning, and driving value through ML

Preferred Skills

• Apache Spark for processing large-scale distributed datasets
• Databricks platform experience
• 4+ years of customer-facing experience in a pre-sales or post-sales role