AI Engineer

About

NeuroHire is building an AI-first SaaS platform to help companies make smarter hiring decisions using real data. AI is not a side feature here  it’s part of the core product, powering matching, ranking, automation, and decision intelligence.

We’re looking for an AI Engineer who can take ideas from concept to production and build systems that actually run, scale, and improve with real usage.

If you enjoy building practical AI systems and shipping them into real products  you’ll fit right in.

What You’ll Work On

Design and build AI systems that power core product features

Develop and deploy machine learning and deep learning models

Build LLM-based workflows using prompting, embeddings, and retrieval pipelines (RAG)

Work with unstructured data (text, resumes, job descriptions) to extract insights

Create scalable inference pipelines optimized for performance and cost

Integrate AI capabilities into backend services and APIs

Monitor models in production and continuously improve performance

Identify edge cases, bias, and failure modes early

Contribute to AI architecture and system design as the platform scales

What We’re Looking For

0 to 2 years of experience building AI/ML systems in production

Strong foundation in machine learning and deep learning

Proficiency in Python and frameworks like PyTorch, TensorFlow, or scikit-learn

Experience with transformers, embeddings, and modern AI architectures

Familiarity with LLMs and building AI-powered applications

Experience deploying models on cloud platforms (AWS, GCP, or Azure)

Understanding of MLOps concepts such as model versioning and monitoring

Ability to work with messy, real-world datasets

Strong problem-solving mindset and ownership

Nice to Have (Not Required)

Experience with generative AI or LLM-based applications

Familiarity with vector databases or retrieval systems

Experience optimizing inference pipelines at scale

Background in SaaS or product-based companies

Knowledge of responsible AI and model explainability