SquarePeg.ai is building cutting-edge AI tools that are transforming job applications and resume review processes to fix the broken job application process where billions of hours are wasted on mismatched applications, biased screening, and manual resume review.
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)
Responsibilities
- 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 our 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
Other
- Opinionated
- Data driven
- Intellectually curious
- Thrive in an environment where you experiment and move quickly
- Strong sense of ownership; Can work autonomously
