Applied AI Research Engineer – Large Language Models

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7jv812

Equixly is an Italian cybersecurity company founded to revolutionise API security through proprietary artificial intelligence and machine learning. Our platform automates API Security Testing, enabling companies to identify deep vulnerabilities rapidly, scalably, and continuously.

We are expanding our AI Team with researchers and engineers who want to work on real, production-grade LLM systems and applied AI challenges.

The role

We are looking for an Applied AI Research Engineer to improve the efficiency and performance of the Large Language Models powering Equixly’s platform.

You will experiment with LLM inference, quantisation, distillation, and low-precision training, turning promising research into validated prototypes and production-ready model improvements. The focus of this role is applied model research rather than DevOps or MLOps. You will report to the Head of AI.

What you will do

- Experiment with and optimise LLM inference using vLLM.

- Evaluate quantisation methods, with particular attention to FP8 and NVFP4, balancing speed, memory usage, and model quality.

- Develop and test model distillation and low-precision training or fine-tuning strategies.

- Benchmark model latency, throughput, memory consumption, and quality using reproducible experiments.

- Collaborate with AI engineers to integrate successful methods into Equixly’s products.

What we are looking for





- PhD in Computer Science, with a research focus on Artificial Intelligence, Machine Learning, Natural Language Processing, or a related area.

- Practical experience training, fine-tuning, evaluating, or optimising Large Language Models.

- Strong Python and PyTorch skills, with experience using Hugging Face Transformers or similar libraries.

- Hands-on knowledge of vLLM or comparable LLM inference frameworks.

- Understanding of model quantisation, particularly FP8, NVFP4, and low-precision model training or fine-tuning.

- Familiarity with knowledge distillation and model compression techniques.

- Ability to design rigorous experiments, analyse results, and communicate findings clearly in English.

Nice to have

- Experience with GPU profiling or distributed model training.

- Knowledge of cybersecurity, API security, agentic AI, or reasoning models.

- Publications or applied research experience in efficient deep learning or Large Language Models.

What we offer

- A stimulating environment at the intersection of cybersecurity and applied AI.

- The opportunity to turn research ideas into measurable improvements to production LLM systems.

- Professional growth within a fast-evolving AI Team.

- Competitive compensation commensurate with experience, plus company benefits.

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7jv812