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Principal Software Engineer LLM Services
4 months ago
Obsidian Security was founded in 2017 to solve the unaddressed blindspot of SaaS Security. SaaS applications provide the tools employees need to succeed and hold the business' most critical information. If those tools become unavailable or that data is jeopardized, there is a detrimental impact on the organization.
Obsidian proudly offers the industry's most comprehensive and powerful SaaS defense solution. We are committed to solving the challenge of SaaS Security for our customers as efficiently and effectively as possible.
We're a passionate team optimizing for impact by solving some of the biggest challenges in cybersecurity today. We listen closely to our customers, iterate quickly, and (over) deliver to
delight them. Working at Obsidian means contributing to an industry-leading cybersecurity product in an environment where customer satisfaction, privacy, and data ethics are paramount.
About the role:
- In your role as a Principal Software Engineer, you will focus on leveraging and optimizing Large Language Models (LLMs) along with the implementation of advanced AI technologies.
- Your key responsibilities will include:
- Development and Optimization of LLMs: Implement and fine-tune state-of-the-art Large Language Models for various applications, focusing on performance and accuracy.
- Evaluating Model Performance: Conduct rigorous evaluations of LLMs, assessing effectiveness, efficiency, and business alignment.
- Integration of Advanced AI Technologies: Implement Retrieval-Augmented Generation (RAG), function calling, and code interpreter technologies to enhance the capabilities of Large Language Models.
- Research and Development: Stay abreast of the latest advancements in machine learning, particularly in LLMs, LLM agents, and large-scale neural network training.
- Data and Model Parallel Training: Utilize data and model parallel training techniques for efficient handling of large-scale models.
- GPU Cluster Management for Training: Oversee extensive training jobs on GPU clusters, ensuring optimal resource utilization for complex tasks.
- Cross-Functional Collaboration and Leadership: Work with ML engineers, data scientists, and product teams, providing guidance and mentorship.
- Documentation and Reporting: Maintain detailed documentation of methodologies, models, and results, communicating findings across the organization.
- Bachelor's degree in Computer Science, Engineering, or related field. Advantage for Master's or PhD in Computer Science, AI, Linguistics, or related fields, with a focus on machine learning and natural language processing.
- Must have working experience within Cyber Security and/or Compliance.
- Experience with LLMs and Python: Extensive experience with python and proficiency in leveraging LLM's.
- Expertise in Parallel Training and GPU Cluster Management: Some background in parallel training methods and managing large-scale training jobs on GPU clusters.
- Analytical and Problem-Solving Skills: Ability to address complex challenges in model training and optimization.
- Leadership and Mentorship Capabilities: Proven leadership in guiding projects and mentoring team members.
- Communication and Collaboration Skills: Effective communication skills for conveying technical concepts and collaborating with cross-functional teams.
- Innovation and Continuous Learning: Passion for staying updated with the latest trends in AI and machine learning.
Our competitive benefits packages are designed to support our employees' well-being, both at work and at home.
- Competitive compensation with equity and 401k
- Comprehensive healthcare with dental and vision coverage
- Flexible paid time off and paid holiday time off
- 12 weeks of new parent or family leave
- Personal and professional development resources
At Obsidian, we are proud to be an equal-opportunity employer. We value diversity and hire for talent, passion, and compassion. In compliance with federal law, all persons hired will be required to submit satisfactory proof of identity and legal authorization
