About the role

Position: ML Architect Engagement Mode: Not specified Location: Not specified Position 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 (Bonus) 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