About the Company

Account Executives need help with selling technically complex products. Sales Engineers are expensive. Meet Docket, the AI agent that serves as a virtual sales engineer for Account Executives.

Docket learns from all unstructured and conversational knowledge within the company, powered by state-of-the-art LLMs, and creates a dynamic knowledge graph. Integrating deep into AE workflow, Docket delivers just-in-time knowledge to ask the right discovery questions and answer complex product questions.

About the Role

• Research and Development: Drive the development of novel models focusing on generative AI. Experiment with the latest advancements in the field and implement state-of-the-art techniques
• Algorithm Design and Implementation: Design and implement advanced machine learning algorithms for natural language understanding and generation. Write scalable, robust, and fully tested software for deployment in mission-critical production environments
• Model Training and Optimization: Design and develop the next-generation data pipeline architecture for powering Docket’s AI models. Oversee the training and optimization of language models, ensuring high performance, efficiency, and scalability.
• Leadership and Collaboration: Lead and inspire a team of machine learning engineers and researchers, fostering a culture of collaboration, creativity, and excellence. Collaborate with CTO and cross-functional teams, including software engineers, data scientists, and product managers, to integrate ML solutions into our products.
• Innovation: Lead research initiatives to explore new ideas and technologies that could enhance our generative AI capabilities. Become an industry expert in data pipeline and model-building architectures

Key Responsibilities

1. Strategy Development: Lead the development of the AI systems that aligns with the company’s vision and market needs. Analyze current trends and technologies to continually position our AI-driven product at the forefront of the industry.
2. Formulate AI strategy for the business in collaboration with the founders
3. Lead R&D for identifying and maintaining defensible AI moat (data/algorithms/papers/IP etc)
4. Establish baselines, measure and improve key AI metrics impacting business
5. Own business-critical AI services
6. Attract and retain top AI talent
7. Engage in hands-on experimentation and identify market trends and strategic opportunities early on
8. Go-to-market messaging for AI initiatives

Qualifications

• Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related field
• Proven experience in building large-scale machine-learning projects in production (ideally NLP projects)
• Strong background in generative AI, natural language processing, and language model development
• Expertise in deep learning frameworks such as TensorFlow or PyTorch
• Excellent communication and collaboration skills
• Strong experimentation and problem-solving mindset
• Published research in reputable conferences or journals related to machine learning and AI is a plus
• Experience managing the ML model lifecycle is a plus