Sr Machine Learning Engineer, AI Research
Design, train, and productionize ML models and pipelines for AI-enabled security/observability platforms. Requires 4+ years experience with Python, PyTorch/TensorFlow, and modern ML techniques.
Responsibilities
- Design, train, and evaluate machine learning models across 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; track results, document findings, and share learnings with the broader team
- Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
Requirements
- 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; 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-Haves
- Master's or PhD degree
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