We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

AI / NLP Engineer at SquarePeg. Remote Location: Remote - US. AI / NLP Engineer. SquarePeg.ai. | Remote | Early Stage Startup. Join . SquarePeg.ai. , a fast-growing HR Tech startup that's already captured 50+ customers just months after launching in 2025. Backed by top-tier investors, we're building cutting-edge AI tools that are transforming job applications and resume review processes—and we need a versatile NLP Engineer to help us scale our impact.. What You'll Build. As our AI Engineer specializing in Data & ML, you'll be the technical force behind our core matching algorithms. You'll work directly with our founding team of 12 to enhance the AI systems that connect the right candidates with the right opportunities.. What You'll Do. NLP for Matching & Scoring. 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. Entity Resolution & Data Engineering. 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. Product Impact. Collaborate directly with our 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. What You Bring. Technical Expertise:. 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. Startup DNA:. Opinionated. Data driven. Intellectually curious. Thrive in an environment where you experiment and move quickly. Strong sense of ownership; Can work autonomously. Why . SquarePeg.ai. ?. Growth opportunity:. 50 customers in just 7 months—we're solving a real problem that the market desperately needs. Backed by the Best:. Top-tier investor support from Next Frontier Capital, Acadian Ventures, and others. Direct Impact:. In a team of 12, your work directly shapes product direction and company success. Ground Floor Opportunity:. Shape our technical foundation and product as we scale. Cutting-Edge Tech:. Work with the latest in AI/ML, from GPT5 to custom transformer architectures. Ready to Reimagine Hiring?. The job application process is broken—billions of hours wasted on mismatched applications, biased screening, and manual resume review. We're building the AI that fixes it.. If you're excited about using your technical skills to create meaningful change in how people find their next opportunity, we want to hear from you.. This role offers competitive salary, equity, comprehensive benefits, and the chance to be a key player in the future of work.