Senior Fullstack AI Engineer - Agents
Vannevar LabsFull Time
Senior (5 to 8 years)
Candidates should have 2+ years of experience as a Staff Engineer, Principal Engineer, or equivalent, and over 5 years of industry experience in AI or Machine Learning Engineering. Proven ability to design, build, and ship production-ready systems is required, along with proficiency in an ML framework of choice and strong coding skills in languages such as Python, Go, Java, or C++. Experience with agentic frameworks, reinforcement learning, natural language processing, or other large ML systems is necessary. A proactive, positive attitude and the ability to thrive in a customer-focused, cross-functional environment are also essential.
The Machine Learning Engineer will provide expert-level individual contributions and thought leadership to build the next generation of intelligent enterprise AI assistants and autonomous AI agents. This includes working at the intersection of applied research and production engineering in areas such as agentic frameworks, LLM orchestration, low latency LLM inference and optimization, domain adapted and memory augmented LLMs, reinforcement learning, and building evaluation frameworks for complex enterprise tasks. Responsibilities also involve building frameworks for LLM-powered agents, inventing new agentic architectures, designing and optimizing reinforcement learning and fine-tuning approaches, leading the development of scalable evaluation and optimization loops, driving technical strategy, mentoring other engineers, and writing robust, maintainable, and well-tested code.
AI-powered search tool for workplace productivity
Glean enhances workplace productivity by providing an AI-powered search tool that works across all applications within a company. This tool utilizes deep learning-based Language Models to understand natural language queries, allowing users to find information more easily. It continuously learns from the specific language and context of a company, improving the relevance of search results without manual adjustments. Additionally, Glean offers a chat assistant that can analyze and summarize information from various company documents and conversations, further increasing efficiency. Unlike many competitors, Glean's focus on natural language processing and its ability to adapt to a company's unique context set it apart. The goal of Glean is to streamline information retrieval in the workplace, making it accessible and efficient for all types of organizations, from startups to large enterprises.