Role : Research Engineer - AI Security

Location : Bengaluru, India

Function : AI Security - Technology & Innovation Centre (TIC)

Employment Type : Full-time

Role Purpose :

The Research Engineer - AI Security is responsible for building, automating, and scaling experimental infrastructure that enables rigorous, reproducible AI security research. The role focuses on experiment automation, benchmarking, and research-to-solution engineering to support secure, compliant, and trustworthy AI systems.

Key Responsibilities :

- Design and implement reproducible experiment pipelines for AI security research.
- Build automation frameworks for benchmarking, ablation studies, and large-scale model evaluations.
- Develop experimental benches for model fingerprinting, mechanistic analysis, unlearning, and provenance.
- Translate research prototypes into engineering-grade proof-of-concepts and reusable components.
- Collaborate with applied researchers, backend engineers, and MLOps teams to enable deployment-ready solutions.
- Maintain experiment tracking, versioning, and validation to ensure reliability and auditability.
- Contribute to technical documentation, evaluation reports, and research artefacts.

Required Qualifications &

Experience :

Education :





- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related engineering discipline.

Experience :

- 3 - 6 years of experience in research engineering, ML engineering, or experimentation-heavy roles.
- Hands-on experience supporting AI/ML research with scalable engineering systems.

Required Technical Skills :

- Robust proficiency in Python and deep learning frameworks such as PyTorch.
- Experience working with large language models, fine-tuning workflows, and adapter-based methods (e.g., LoRA).
- Understanding of model internals including parameters, activations, embeddings, and output distributions.
- Experience with experiment tracking, benchmarking, and reproducible research workflows.
- Familiarity with AI security, ML robustness, model analysis, or privacy-related techniques is desirable.

Success Indicators :

- Delivery of reliable, repeatable experimental infrastructure supporting AI security research.
- Effective enablement of applied researchers through automation and tooling.
- Successful transition of research outputs into deployable proof-of-concepts or platform components

📌 Ekfrazo Technologies - Research Engineer - AI Security (India)
🏢 Ekfrazo Technologies Private
📍 India