Senior Clinical Data Manager
Precision For Medicine
Job Level
Mid-LevelSenior
Tech Stack
AWSCassandraCloudCyber SecurityDockerElasticSearchGoKafkaKubernetesMicroservicesPythonPyTorchTensorflow
About the role
- Design and develop LLM-based models for integration into Charlotte AI, focusing on practical applications that enhance security analyst workflows and decision-making
- Research and prototype new AI/ML techniques to expand Charlotte AI's capabilities in areas like threat reasoning, incident summarization, and interactive security analysis
- Build and optimize data pipelines for training custom LLMs on security-specific datasets, ensuring high-quality model performance in production environments
- Implement mechanistic explainability and interpretability features to ensure Charlotte AI's recommendations are transparent and trustworthy for security professionals
- Collaborate with engineering teams to translate ML innovations into scalable, fault-tolerant microservices using modern cloud technologies
- Continuously monitor and improve model performance through rigorous testing, A/B experimentation, and deployment of updated fine-tuned models
- Work with massive-scale security data (processing 3 trillion events daily) to extract actionable insights and identify emerging threat patterns
- Partner with product managers and security experts to align model capabilities with real-world security operations needs
- Contribute to the broader ML community through publications, patents, and open-source contributions while maintaining CrowdStrike's thought leadership in AI-powered security
Requirements
- 5+ years of applied machine learning experience developing and deploying production ML systems
- Strong foundation in machine learning fundamentals, including GenAI, deep learning, natural language processing, and statistical methods
- Hands-on experience with LLMs and frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers
- Proficiency in Python and experience with distributed computing environments
- Experience with production ML pipelines, including data preprocessing, model training, evaluation, and deployment
- Strong problem-solving skills with the ability to translate complex security challenges into ML solutions
- Excellent communication skills to collaborate with cross-functional teams and explain technical concepts to diverse audiences
- Self-starter mentality with a passion for continuous learning and staying current with AI/ML advances
- (Bonus) PhD or advanced degree in Computer Science, Statistics, Mathematics, or related field with focus on ML/AI
- (Bonus) Experience with security or cybersecurity domains
- (Bonus) Expertise in specialized areas: self-supervised learning, representation learning, or multi-modal learning
- (Bonus) Experience with large-scale distributed training and GPU optimization (CUDA, TensorRT)
- (Bonus) Knowledge of cloud technologies (AWS, Kubernetes, Docker) and microservices architecture
- (Bonus) Familiarity with big data technologies (Kafka, Cassandra, Elasticsearch)
- (Bonus) Track record of research contributions or patents in AI/ML
- (Bonus) Experience with Go (Golang) for building high-performance systems
- (Bonus) Background in privacy-preserving ML or adversarial machine learning
