(Security) Machine Learning Engineer
Tasks
- Automate SOC tasks with LLMs
- Build security data pipelines for ML ready datasets
- Contribute to detection content using statistical analysis and clustering
- Deploy models into production securely
- Design machine learning models for security detection
- Document model methodologies and performance metrics
- Ensure model outputs are interpretable
- Evaluate LLM outputs with guardrails
- Implement monitoring alerting and retraining
- Integrate ML outputs into SOC workflow
- Process and store security relevant logs and telemetry
- Prototype adversarial ML and automated threat detection
- Tune models to reduce false positives
Perks/Benefits
- Bike allowance
- Flexible working
- Generous leave
- Health coverage
- In-person collaboration
- Learning and development
- Lunch and snacks
- Parking support
- Public transport coverage
- Retirement options
- Stock options
- Wellness support
Skills/Tech-stack
Adversarial Machine Learning | Agent Design | Airflow | Anomaly Detection | Authentication logs | Behavioral Modeling | ClickHouse | Data Pipelines | Data Science | EDR | Elasticsearch | Event management | Graph analytics | Kafka | Machine Learning | Model Deployment | Model Evaluation | Model Monitoring | Model Training | Network flow | NumPy | Pandas | Prompt engineering | Python | Redis | Retrieval-Augmented Generation | Security Information | Security Information and Event | Security Information and Event Management | Unsupervised anomaly detection
Education
N/A
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