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Patlytics, Inc.
New York, United States; Toronto, ON, Canada
Source: Patlytics, Inc. careers · View original posting
From Patlytics, Inc.'s posting. “We” and “our” refer to the employer.
Patlytics is the fastest-growing AI-native patent intelligence platform, transforming how IP is protected and monetized at scale. Our advanced LLMs and generative AI engine—custom-built for intellectual property—power every phase of the patent workflow from invention disclosure through litigation, delivering citation-backed insights with unprecedented accuracy and speed.
Fresh off our $40M Series B — led by
SignalFire
, with participation from
N47, Myriad Venture Partners, Liquid 2 Ventures, BAM Corner Point, Alumni Ventures, Antiportfolio Ventures and
Relativity
With teams across the globe we're building a global company fueled by exceptional talent and bold ideas. Our rapid expansion is driven by people who bring entrepreneurial energy, intellectual curiosity, and a shared commitment to setting the global standard for AI-powered IP intelligence. We're creating a culture where diverse perspectives shape breakthrough innovation and every voice contributes to transforming how the world protects ideas.
We hire for trajectory, not just credentials. If you're 70% of this list and hungry to close the gap, apply.
Develop and deploy robust, scalable AI/ML algorithms for cutting-edge IP applications
Design, implement, and iterate on multi-step LLM pipelines for patent claim analysis, infringement detection, and prior art search, including the model selection, prompt architecture, and structured output contracts that define product quality
Build and maintain a rigorous evals framework: define success metrics per pipeline stage, curate golden datasets from real IP cases, and run continuous regression testing to catch degradation before users do
Develop retrieval systems (vector search, BM25 hybrids, re-ranking) optimized for patent corpus characteristics, long documents, technical claim language, biological sequence identifiers
Architect and ship agentic workflows within our Agent layer, coordinating tool use, memory, and multi-turn reasoning over complex IP research tasks
Develop data classification techniques and post-training on the latest LLMs
Collaborate with patent attorneys and domain experts to encode expert judgment into prompts, rubrics, and fine-tuning datasets, then measure whether it worked Own cost, latency, and quality tradeoffs for production inference: prompt caching strategies, context window management, batching, and model migration planning on AWS, GCP and other LLM providers.
Partner with a highly talented cross functional group of researchers, applied scientists, engineers, and product managers to build and evolve the (your company’s platform, product, solution, etc.)
That said, these responsibilities are just the beginning! As we continue to grow, we encourage you to contribute wherever you observe opportunities in the business that align with your interests.
You've shipped LLM-powered features that real users depend on, not just demos or side projects. You have a track record of turning prototype prompts into production pipelines with monitoring and fallbacks
You think in evals first. Before writing a prompt, you ask 'how will we know if this is better?' and you build the scaffolding to answer that question rigorously
You're comfortable with ambiguity at the model layer. You know that Claude, GPT, and Gemini make different tradeoffs, and you've developed intuition for when to switch, fine-tune, or route between them
You write solid Python and have enough backend instincts to own a service end-to-end: API design, data pipelines, async processing, and observability
You can read a patent claim and not immediately give up. You're curious about domain knowledge and willing to become a genuine expert in IP reasoning over time
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