Job Description

Job Description

Job Description

About Garden

Garden (gardenintel.com) accelerates global technological development by fixing the patent system. We're building AI-powered search and analysis tools to make the patent process less painful and more effective for R&D organizations, inventors, prosecutors, and litigators. Our core product, Patentbreaker, is a groundbreaking 102/103 prior art search tool that automates the generation of claims charts for inter-partes reviews.

Leading companies, law firms, and research organizations are already seeing huge efficiency gains from our tools, and we were able to monetize a couple weeks into deploying. But this is just the beginning - our vision is to leverage AI, rich data, and scalable analysis to drive smarter R&D investment decisions across industries. The patent system today is overwhelmed by the explosion of filings, fragmented across service providers, and inaccessible to many inventors. We're here to change that. Our early traction has been incredible, with hundreds of users, a growing enterprise waitlist, and key advisors bought into our mission. Recently, we raised a $6.8m seed round from Spark Capital, Craft Ventures, and top angel investors.

We're a tight-knit, ambitious team of experts in NLP, patents, and product development. We’re incredibly customer obsessed, work in the office 5-6 days a week, and ship on tight timelines. We are a mix of research and product in our work, and seek to find members of our team that are excited by both in a burgeoning industry.

The opportunity is huge, the problem is urgent, and the team is top-notch. If you're an exceptional full-stack/backend engineer who wants a high-impact role at a fast-moving AI startup, we'd love to chat. At Garden, you won't just grow as an engineer - you'll help plant the seeds for a better innovation ecosystem.

As a founding machine learning engineer/researcher, you'll work directly with the CEO to develop and implement advanced AI solutions that form the core of our products. You'll be instrumental in building and scaling our ML infrastructure, designing novel NLP and computer vision retrieval models, and translating research breakthroughs into practical applications. This role requires a deep understanding of machine learning, expertise in handling unstructured data, and proficiency in large language models for complex reasoning tasks. You'll need a passion for solving intricate problems and the ability to navigate the challenges of a fast-growing startup.

Responsibilities:

• Design, implement, and maintain SOTA text and image retrieval models for patent analysis and search, with a focus on processing and understanding unstructured data

• Develop and maintain large-scale data pipelines for cleaning, processing, and analyzing millions of documents and images to improve retrieval accuracy

• Architect and build scalable ML infrastructure to support our growing product suite, with emphasis on efficient handling of unstructured data

• Lead research initiatives to advance our AI capabilities, particularly in the areas of large language models for reasoning tasks and information retrieval

• Collaborate with product and engineering teams to integrate ML solutions into user-facing products

• Contribute to strategic technical decisions and help shape the company's AI roadmap

• Mentor junior team members and contribute to building a world-class AI team

Qualifications:

• Advanced degree (Ph.D. preferred) in Computer Science, Machine Learning, or a related field

• Extensive experience in developing and deploying large-scale NLP and computer vision models, with a focus on handling unstructured data

• Strong background in machine learning, deep learning, and statistical analysis

• Expertise in large language models and their application to complex reasoning tasks

• Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow

• Proven track record of building and scaling data pipelines for processing and cleaning large volumes of unstructured text and image data

• Deep understanding of information retrieval systems and techniques for improving search accuracy

• Strong problem-solving skills and ability to translate research into practical applications

• Excellent communication skills and ability to explain complex technical concepts to non-technical stakeholders

Nice to Have:

• Experience in the legal tech or patent industry

• Background in cheminformatics or computational chemistry

• Familiarity with graph neural networks and knowledge graph construction

• Expertise in transfer learning, few-shot learning, and zero-shot learning techniques

• Experience with MLOps and ML system design

• Contributions to open-source ML projects or relevant research publications

• Experience with multi-modal learning incorporating text, images, and structured data

Compensation: The expected total cash compensation for this role is $250,000 - $400,000 with additional equity and benefits, commensurate with experience and qualifications.

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