1 day ago
Base Salary
$155k - $228k/yr
Responsibilities
- Collaborate with Research Scientists, Engineers, and Data Scientists to build, adapt, optimize, and deploy LLM models in production at very large scale.
- Design and implement robust API services, libraries, and container strategies supporting the end-to-end LLMOps lifecycle.
- Optimize deep learning and LLM training and inference for speed and cost on specialized hardware.
- Drive complex AI problems from research and literature review through data exploration, novel in-house methods, and productization.
Requirements
- M.S. in Computer Science or equivalent experience.
- At least 5 years of experience as a Research Engineer or Machine Learning Engineer.
- Hands-on MLOps/LLMOps experience building, optimizing, deploying, and operating deep learning models using PyTorch, Transformers, and LLMs rather than only 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 infrastructure such as LangGraph, LangFuse, and vector stores.
Benefits
- Hybrid work arrangement with two in-office days each week in the New York City or Arlington, VA office.
- Flexible work arrangements and offices worldwide.
- Generous paid time off and sick leave.
- Competitive benefits package, employee resource groups, manager development programming, and professional development funds.
Tech Stack
Categories
AI ResearchML Engineering
About Dataminr
Dataminr builds an AI-driven platform that detects events, threats, and emerging risks from public data and delivers real-time alerts. Organizations in corporate security, cyber, risk, and the public sector use it to monitor crises, digital risks, and third‑party issues via subscription software and data services. Founded in 2009 and headquartered in New York City, the company is privately held and serves enterprises and government agencies worldwide.