Junior NLP/LLM Researcher

Job Description:

We are seeking a Junior LLM/NLP Researcher to conduct advanced research and develop innovative applications focused on protecting and evaluating LLMs. In this role, you will collaborate with a multidisciplinary team of scientists and engineers, working together to address critical challenges. You will be responsible for designing, implementing, and evaluating new algorithms, models, and agents that help safeguard LLMs.

About DeepKeep:

At DeepKeep, we create a comprehensive solution for safeguarding and evaluating ML applications in multiple fields, including Large Language Models, Computer Vision, and multi-modal applications.

The DeepKeep Platform protects models in real-time from adversarial attacks, problematic outputs and data leakage, while also enabling a wide range of evaluation methods to measure model performance.

We take pride in being on the forefront of technology and always strive to develop and implement the best solutions there are.

Key Responsibilities:

• Develop new and unique evaluation methods: Implement and develop advanced metrics to evaluate LLMs performance on multiple fronts.
• Create real-time protections: Develop innovative methods to detect and mitigate adversarial attacks on LLMs and keep them in line with the user’s requirements such as avoiding hallucinations, leaking personal data etc.
• Research and Development: Conduct research on adversarial attacks, model protections and performance evaluation techniques for NLP models. Explore and develop state-of-the-art methods and propose innovative solutions.
• Collaboration: Work closely with senior team members, participate in brainstorming sessions, and contribute to the team's success.

Qualifications:

• Professional Experience:
• MSc. in Computer Science, Mathematics, or a related data-focused field,
• OR BSc. with at least 1 year of experience in developing NLP models.
• Technical Skills: Proficiency in Python and experience with deep learning frameworks like PyTorch and transformers.
• Strong mathematical background to understand and apply complex concepts. Ability to translate research findings into practical applications.
• Excellent interpersonal skills for effective collaboration and teamwork.
• Advantage - Research Experience in conducting theoretical or experimental research, using statistical tools and mathematical formulations to solve complex problems.
• Advantage - Professional Experience in developing products in production environments, creating features from conception to completion.