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AI / NLP Engineer SquarePeg.ai | Remote | Early Stage Startup Join SquarePeg.ai, a fast-growing HR Tech startup that'...

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Selected role

AI / NLP Engineer

SquarePeg Anywhere

$112k - $132k Senior Full-time

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.

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