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Patlytics

AI Engineer

Patlytics

. Develop and deploy robust, scalable AI/ML algorithms for cutting-edge IP applications .

Posted 4/22/2026full-timeNew York City • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies
AWSCloudGoogle Cloud PlatformPandasPythonScikit-LearnSparkSQL

About the role

Key responsibilities & impact
  • 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.)
  • Work with large, complex data sets, solve difficult, non-routine analysis problems, and apply advanced analytical methods as needed
  • Partner with the Leadership Team to align development strategies with key product requirements and long-term technical roadmap
  • Build tools to monitor data pipeline performance, data quality and models in production
  • Perform unit testing, profiling, and parameter tuning
  • Collaborate with data engineers & platform team to implement data pipelines and robust production real-time and batch decisioning solutions
  • Lead ongoing R&D of new technologies, data sources and data science & optimization tools
  • Improve existing machine learning methodologies by developing new sources and testing enhancements, running computational experiments, and fine-tuning parameters

Requirements

What you’ll need
  • 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
  • You have a strong technical background building ML & AI pipelines
  • You have great understanding of ML methods and statistics, including ML project lifecycle and associated challenges at each stage of development
  • Experience deploying, monitoring and maintaining data science products in cloud environments such as AWS and GCP.
  • Solid understanding of data transformations and analytics functions using tools/languages like (Pandas, Sklearn, SQL, Spark, etc.)
  • Familiarity with database modeling, data warehousing principles and SQL

Benefits

Comp & perks
  • Comprehensive health coverage – Medical, dental, vision, plus FSA, commuter benefits, and health advocacy through Rightway
  • Mental health & wellness support – Access to Spring Health and Headspace, plus "Mental Escape Days" to recharge when you need it
  • Immediate 401(k) enrollment – No waiting period to start saving for your future
  • Generous time off – Unlimited PTO, 12 paid company holidays, plus a full week off during our Holiday Break
  • Family-first policies – Paid parental leave to support you during life's biggest moments
  • Invest in yourself – Professional development budget, gym membership stipend, and learning opportunities
  • Celebrate what matters – Birthday and work anniversary recognition, plus generous employee referral bonuses
  • Hybrid work environment (open to remote pending location), while staying connected with a passionate and talented team

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
AI algorithmsML algorithmsLLM pipelinesdata classification techniquesdata transformationsanalytical methodsunit testingparameter tuningmodel selectionprompt architecture
Soft Skills
collaborationproblem-solvingcuriosityadaptabilitycommunicationleadershipcritical thinkingattention to detailstrategic alignmentevaluation mindset