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Cribl
Sr Machine Learning Engineer, AI Research
Cribl
Anywhere•Remote•Salary•4-7 Yrs•1 hour ago
Job description
AI ResearchMachine Learning EngineerMLOpsNLPComputer Vision
Overview
Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what's next.
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
Qualifications
- Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 4+ 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
Nice to have
- Experience with rapid iteration and experimentation in production environments
- Knowledge of latest research papers or emerging trends in the field
- Experience mentoring junior engineers in ML systems or practices
- Understanding of how AI impacts enterprise IT and security operations
Education
- Bachelor's degree preferred in Computer Science, Mathematics, Statistics, or related field
- Master's or PhD preferred but not required