About the Role:
CrowdStrike is actively looking for Data Scientists to join our team building the next generation of AI assistants powered by large language models (LLMs). You will work closely with other scientists, software engineers and product managers to guide the development of our assistants' underlying ML models and capabilities. We provide a fast-paced, innovative environment to create technology that improves people's lives. This is a unique opportunity to play an integral role in developing AI assistants that will revolutionize how we access information and interact with technology. Working collaboratively with a multidisciplinary team, you'll apply your insights to tackle complex cybersecurity problems.This opportunity presents a dynamic, growth-oriented startup environment for a driven, research-focused professional.
What You'll Do:
Research and prototype new AI/ML techniques to expand assistants' knowledge and skills in areas like reasoning, summarization, and interactivity
Design, develop, and productionize LLM-based models for integration into our industry-leading virtual assistant platform
Utilize large-scale, high-dimensional data to generate actionable insights, identify patterns, and visualize trends.
Continuously collect data, monitor, and improve assistant performance through testing and deployment of updated self-hosted fine-tuned models
Establish scalable ML architecture and pipelines to deploy large language model innovations into 24/7 production environments
Collaborate cross-functionally to align model updates with product roadmap and user needs
Disseminate findings through publications and presentations, bolstering CrowdStrike's thought leadership in AI/ML applications in cybersecurity
Collaborate with other data scientists and engineers, nurturing a culture of continuous learning and curiosity.
What You'll Need:
Applied machine learning research expertise (2+ years) developing and deploying production systems.
Skilled at extracting actionable insights from large, high-dimensional, sparse data across the machine learning pipeline and driving real-world impact.
Self-starter with a thirst for new challenges and technologies
Comfortable with Python, Deep Learning frameworks (e.g. Tensorflow, Pytorch) and cloud technologies in a Linux environment
Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
Familiarity with GPU based technologies like CUDA, CuDNN and TensorRT
Interested to dive into the field of cybersecurity
Excellent communicator with the ability to simplify complex concepts
Robust problem-solving and critical-thinking skills
Bonus Points:
PhD in Computer Science, Statistics, Mathematics, or a related field, with a focus on data science, machine learning or AI
Track record of research contributions, preferably in high-impact, peer-reviewed scientific journals in the field of AI/ML.
