Staff Machine Learning Engineer, AI Researcher

Cribl

1d•$230,000 - $275,000•Remote

About The Position

Cribl does differently. What does that mean? It means we are a serious company that doesn’t take itself too seriously; and we’re looking for people who love to get stuff done, and laugh a bit along the way. We’re growing rapidly - looking for collaborative, curious, and motivated team members who are passionate about putting customers first. As a remote-first company we believe in empowering our employees to do their best work, wherever they are. As the data engine for IT and Security many of the biggest names in the most demanding industries trust Cribl to solve their most pressing data needs. Ready to do the best work of your career? Join the herd and unlock your opportunity. Why You'll Love This Role You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems. You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers. On top of it all you will have fun. Cribl strives to be a great place to work for everyone.

Requirements

Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 5+ years of industry or research experience (Master's or PhD a plus)
Deep hands-on experience training and evaluating ML models, including language models
Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar)
Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques
Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize
Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders

Responsibilities

Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones