Applied ML Engineer, Vultron

• Experience with Large Language Models
• Experience at an elite AI research institution
• Experience working in complex AI domains (e.g. search, knowledge graphs, LLM evaluations)
• Extreme care about the end user experience and take pride in building exceptional products
• Demonstrated passion for start-ups or early-stage companies
• At least 3 years of experience in ML engineering, research, or similar domains
• Experience designing and building machine learning systems

• We are harnessing the transformative power of Generative AI and autonomous technology to revolutionize the way things are done, breaking away from old methods to significantly improve efficiency, security, and creativity in all kinds of government-related initiatives
• Handling Sensitive Data: Dealing with highly confidential information from critical government contracting firms
• Pushing AI Frontiers: Solving problems that surpass the scope of current AI benchmarks in the government context
• Uncharted Territory: Addressing unique challenges in natural language processing and optimizing AI models for specific government contracting functions, while ensuring secure and compliant data handling
• Build and improve AI powered product features
• Enhance the accuracy and consistency of AI generated outputs
• Develop and refine semantic retrieval systems based on RAG, Knowledge Graphs and other techniques
• Develop systems to collect and index government datasets
• Address some of the world's most challenging unsolved research and engineering issues, particularly those related to large language models (LLMs) in production

Total funding: $4.9m

Securing federal contracts is essential for national growth, yet the process can be daunting. For example, in FY23 the US spent $774.6 billion, awarding contracts to nearly 110,000 companies. However, preparing proposals in response to government Requests for Proposals (RFPs) can be both time-consuming and expensive.