Tigera
Network Security
SeniorML/AIEngineer
“Senior ML/AI Engineer at Tigera. Skills: Machine Learning, Applied AI, LLMs, Security. Own the machine learning. applied AI side of this product”
What You'll Achieve.
prevent; detect; mitigate security breaches; turning telemetry into detections; risk scores; behavioural baselines
Industry & Context.
detecting agents at runtime; understanding their behaviour; distinguishing legitimate activity from misbehaviour; giving security teams controls; problems machine learning; distributed systems; applied AI; security research
External visibility can also be part of the role, publish your research, speak at conferences, represent Tigera in technical community
What They're Looking For.
Must Have
5+ years of professional ML engineering experience, at least two years building and deploying production ML systems, fundamentals in classical machine learning, gradient-boosted trees, regression, classification, evaluation methodology, feature engineering, dealing with class imbalance and noisy labels, Experience with anomaly detection or time-series modelling, Hands-on experience using LLMs for applied tasks, function calling, retrieval-augmented generation, prompt engineering, fine-tuning, evaluation, Python, standard ML ecosystem, scikit-learn, PyTorch or TensorFlow, pandas, Comfort working with large-scale telemetry data, ClickHouse, BigQuery, Snowflake, Spark, communication skills, excellent writing skills
Nice to Have
Prior experience in security, infrastructure, systems-adjacent ML, Familiarity with eBPF, kernel telemetry, low-level systems observability, Experience deploying ML models in latency-sensitive paths, sub-millisecond inference, Open-source contributions to ML tooling, applied AI projects, Experience with model versioning, MLflow, Weights & Biases, BentoML, Background in interpretable ML
What You'll Do.
Own the machine learning
applied AI side of this product
turning agent telemetry into detections
behavioural baselines
classification from runtime telemetry
behavioural threat detection
using LLMs to bridge gap
AI/ML voice in architecture decisions
A/B testing of detection models
design data infrastructure
How You'll Work.
Team & Collaboration
respecting; collaborating; supporting each other; AI/ML voice in broader architecture decisions; work with product team
Communication Scope
communication skills; excellent writing skills
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