AI / Machine Learning Engineer

CVgenix is an AI-powered recruiting platform redefining how companies find, evaluate, and engage talent. We build intelligent systems that understand candidates beyond keywords —

using LLMs, embeddings, and predictive models to deliver accurate matching, candidate scoring, and automated recruiter workflows.

As an early-stage startup, we move fast, experiment boldly, and give engineers real ownership over product and architecture.

Role Overview

We’re looking for an AI / ML Engineer to design, build, and scale the core intelligence behind

CVgenix. You’ll work on candidate–job matching, CV parsing, ranking algorithms,

LLM-powered interactions, and learning systems that continuously improve hiring outcomes.

You’ll collaborate closely with product, backend, and design teams and directly influence the future of our AI architecture.

Responsibilities

● Design and develop ML models for candidate–job matching, scoring, and ranking

● Build and optimize CV parsing and data extraction pipelines

● Implement LLM-based features (semantic search, candidate summaries, recruiter copilots)

● Work with embeddings, vector databases, and semantic similarity models

● Train, evaluate, and deploy ML models in production environments

● Improve model performance using feedback loops and real hiring data

● Collaborate with backend engineers to integrate AI services into the platform

● Ensure scalability, performance, and reliability of AI systems

● Stay up to date with the latest AI/ML and LLM advancements

Required Skills & Experience

● 3+ years of experience in Machine Learning or Applied AI

● Strong knowledge of Python and ML frameworks (PyTorch, TensorFlow, or similar)

● Experience with NLP, text embeddings, or semantic search

● Hands-on experience with LLMs (OpenAI, open-source models, fine-tuning, prompt engineering)

● Solid understanding of ML evaluation metrics and experimentation

● Experience deploying ML models to production

● Familiarity with SQL/NoSQL databases and data pipelines

● Ability to work independently in a fast-paced startup environment

Nice to Have

● Experience with HR Tech, recruiting platforms, or recommendation systems

● Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus)

● Experience with MLOps tools and pipelines

● Background in information retrieval or ranking systems

● Startup or early-stage product experience