Key skills
MLOps/LLMOps ExperienceDeep Learning modelsNatural Language ProcessingPythonContainersKubernetesAWSDatabricksGenerative AIComputer VisionKnowledge RepresentationVector DatabasesAgentic infraAIMachine LearningDeep LearningLLMPyTorchMLOpsLangGraph
About this role
Dataminr is a mission-driven team of talented builders, creators, and visionaries focused on real-world impact through AI-powered intelligence solutions. In this role, you will collaborate with Research Scientists and Data Scientists to develop and deploy advanced AI models, tackling complex challenges and optimizing performance in a large-scale environment.
Responsibilities:
- Work with groups of Research Scientists, Engineers, and Data Scientists in the AI Platform organization and beyond, to deploy, build, adapt, optimize, and deploy LLM models in production at very large scale
- Own the technical design and implementation of robust API services, libraries, and container strategies that define and support our end-to-end LLMOps lifecycle
- Optimize DL/LLM training and inference performance (speed/cost) on specialized hardware
- Drive the full lifecycle of complex AI problems: from initial research and literature review to hands-on data exploration, implementation of novel, in-house methods, and successful productization
Requirements:
- M.S. in Computer science or equivalent experience
- 5+ years of experience as a Research or Machine Learning Engineer
- MLOps/LLMOps Experience: building, optimizing, deploying and operating Deep Learning models using PyTorch, including Transformers and LLMs, not just using APIs
- Experience working with Research Scientists, reading technical research papers, and implementing state-of-the-art methods in Natural Language Processing, Computer Vision, Knowledge Representation and Management, Vector Databases and Generative AI
- Expertise in Python
- Experience with Containers, Kubernetes, AWS, Databricks, and Agentic infra such as LangGraph, LangFuse, and vector stores