SquarePeg

AI/NLP Engineer

SquarePeg

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AWSBootstrapCloudGoogle Cloud PlatformPythonPyTorchScikit-LearnSQLTensorflow

About the role

  • Be the technical force behind our core matching algorithms and work directly with the founding team of 12
  • Build and maintain taxonomies for candidate and job attributes; bootstrap gold datasets and evaluation pipelines
  • Extract and normalize entities from resumes and job descriptions; craft and optimize prompts and fine-tuned models
  • Develop and refine retrieval, ranking, and scoring using embedding-based methods and LLMs
  • Refine proprietary scoring algorithms that evaluate candidate-job compatibility
  • Conduct deep-dive analyses to identify patterns in successful hires and optimize our recommendation engine
  • Implement innovative NLP solutions that understand context, intent, and nuance in hiring language
  • Design and implement robust data pipelines that can handle massive volumes of resume and job posting data
  • Build sophisticated entity resolution systems to normalize and deduplicate candidate profiles across multiple data sources
  • Create scalable data architectures that power real-time matching at scale
  • Collaborate directly with product team to translate business requirements into technical solutions
  • Own the end-to-end ML lifecycle from experimentation to production deployment
  • Continuously iterate on algorithms based on customer feedback and performance metrics

Requirements

  • Deep understanding of machine learning algorithms, particularly in recommendation systems or ranking problems
  • Experience with prompt engineering, prompt chaining, and LLM fine-tuning
  • Knowledge of vector databases and semantic search technologies
  • Familiarity with A/B testing and experimental design
  • 3+ years of hands-on experience with Python, SQL, and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)
  • Proven track record in NLP and working with large language models (OpenAI, Anthropic, open-source LLMs)
  • Experience with data engineering tools and cloud platforms (AWS, GCP)
  • Strong background in entity resolution, data matching, or similar deduplication challenges
  • Building and maintaining ontologies
  • Building datasets and evaluation pipelines
  • Choosing different methods based on tradeoffs of cost, latency, and accuracy
  • Opinionated
  • Data driven
  • Intellectually curious
  • Thrive in an environment where you experiment and move quickly
  • Strong sense of ownership; Can work autonomously