SDE 2 AI/ML

Role Overview

We’re hiring an SDE2 AI/ML to drive the development of machine learning and generative AI capabilities that power our cybersecurity platform. You’ll work closely with founders and product teams to build scalable AI models, pipelines, and integrations that enhance threat detection, automation, and user experience.

What You’ll Do

• Architect, develop, and deploy ML models for security telemetry analysis, anomaly detection, and risk scoring.
• Build generative AI solutions (e.g., LLMs, prompt engineering, chatbots) to assist in security automation and contextual threat insights.
• Own end-to-end ML workflows: data ingestion, feature engineering, model training, evaluation, and deployment.
• Collaborate with product, backend, and frontend teams to integrate AI models into scalable production services.
• Optimize model performance, including latency, accuracy, and resource utilization for real-time use cases.
• Lead code reviews, mentorship, and AI best practices adoption across the engineering team.
• Stay informed on the latest advances in ML, deep learning, and generative AI and apply them to product challenges.

What We’re Looking For

• 3+ years in building production AI/ML systems.
• Cybersecurity experience is a must.
• Strong expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and understanding of model architectures (transformers, CNNs, RNNs).
• Experience in generative AI including large language models, prompt engineering, and fine-tuning techniques.
• Proficiency in Python and related tools for ML and data processing. Familiarity with Go or other backend languages is a plus.
• Solid background in data engineering: ETL pipelines, feature stores, and model deployment on cloud or on-prem infrastructure.
• Ability to translate complex ML concepts into scalable, maintainable code and user-facing features.
• Experience working in a fast-paced startup or product environment with cross-functional collaboration.

What’s In It For You

• Work on cutting-edge AI/ML technologies applied to cybersecurity problems.
• Influence product direction and AI roadmap closely with founders and architects.
• High ownership culture with rapid iteration and learning opportunities.
• Career growth into AI/MLEM/Director roles as the company scales.