Member of Technical Staff

Who We Are:

Prophet Security is a VC-backed start-up building technologies that leverage generative AI technology to streamline the triage and investigation of security alerts in enterprises. We are looking for talented Backend Software Engineers to join as a core members of our founding engineering team, where your contributions will significantly shape our architecture and key technical decisions.

Prophet Security’s founding team has over 30 years of experience in cybersecurity at leading companies including Abnormal Security, Expel, Madiant, McAfee, Oracle, Red Canary, Red Hat, Riverbed, and Symantec and are now focused on the Large market opportunity with the potential to disrupt the $400B security labor market.

Job Duties:

• Work on the integration and optimization of large language models (LLMs) and AI/ML technologies into product.

• Lead the design and development of innovative features using LLMs.

• Master the art of prompt engineering, fine-tuning, and in-context learning to maximize the potential of LLMs within our product.

• Develop a model evaluation framework, extending benchmarks like MT-Bench to ensure the robustness and performance of LLM implementations.

• Establish comprehensive guardrails for safe and responsible use of LLMs, proactively mitigating potential risks.

• Shape the architecture of LLM solutions, making strategic decisions on model configurability, portability, and cost.

• Stay at the forefront of LLM research, identifying groundbreaking techniques and tools to enhance product offerings.

Education and Experience required:

Master’s degree in Computer Science, Computer Engineering, Computational Mathematics, Statistics, Data Science, or a closely related field and 4 years as a Software Engineer, Machine Learning Engineer, Data Scientist/Analyst, Research Scientist, Applied Scientist, or Quantitative Analyst.

Background:

Position requires three (3) years in all of the following:

1) Developing and maintaining software and machine learning (ML) applications using Golang and Python;

2) Developing, fine-tuning, model evaluating, and deploying Large Language Models (LLMs), using frameworks like Hugging Face Transformers, OpenAI GPT, or similar technology;

3) Cloud platforms, including AWS and Azure, with experience in deploying and managing hosted LLM services for production ML environments;

4) Classical and deep learning based Natural Language Processing (NLP) models;     

5) Implementation of deep learning algorithms using TensorFlow or Pytorch framework;

6) Evaluation of NLP models for classification and sequence prediction problems;

7) Shipping LLM-powered products or features;

8) Translating LLM research concepts into practical applications while keeping in mind safety considerations;

9) Designing and scaling ML systems for optimizing performance, user experience, and resource utilization;

10) Prompting Techniques: Chain-of-Thought (CoT), Tree of Thoughts (ToT), ReAct, or other advanced prompting strategy;

11) Retrieval-Augmented Generation (RAG) or similar technique; and

12) Delivering technical presentations.

Location:

The person who fills this role may work remotely from anywhere in the U.S. (HQ: Atherton, CA)