Our Mission
At Palo Alto Networks, we're united by a shared missionto protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you're ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you're in the right place.
Who We Are
In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!
We believe collaboration thrives in person. That's why most of our teams work from the office full time, with flexibility when it's needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.
Job Summary
The Team
Engineering - The Engineering team is at the core of our products and services. We are a team of innovators, problem-solvers, and builders who are passionate about creating cutting-edge cybersecurity solutions. We work collaboratively to tackle complex challenges, from cloud-native security to threat intelligence and endpoint protection. Our work is critical to protecting our customers digital way of life.
Job Summary
Join our team building a cutting-edge multi-tenanted GenAI Security Platform that helps organisations validate and secure their AI systems against adversarial attacks. We're looking for a motivated junior ML engineer to contribute to research automation, LLM evaluation systems, and novel attack discovery while learning production ML engineering.
Key Responsibilities
- Build pipelines for discovering and analyzing novel jailbreak techniques and attack patterns.
- Develop intelligent scoring and classification systems using LLM-as-judge patterns.
- Create multi-turn conversation agents and evaluation workflows.
- Design and optimize prompt templates for various evaluation tasks.
- Work with embeddings and vector similarity for novelty detection and deduplication.
- Run ML experiments, analyze results, and contribute to research initiatives.
- Implement LLM-based evaluation and classification systems with guidance from senior engineers.
- Build and test prompt templates for structured output generation and chain-of-thought reasoning.
- Develop semantic similarity pipelines using embeddings for pattern matching and clustering.
- Create data processing scripts for evaluation results and knowledge extraction.
- Design and run experiments to test new hypotheses and attack techniques.
- Work with vector databases for storing and querying embeddings.
- Contribute to research automation tools and novel technique discovery.
- Write tests, document experiments, and participate in code reviews.
Qualifications
Required Qualifications
- 0-1 years of professional experience (internships, research assistantships count).
- Strong Python programming skills with an understanding of ML workflows.
- Basic understanding of LLMs, transformers, and embeddings.
- Familiarity with prompt engineering and LLM capabilities/limitations.
- Understanding of experimental design, evaluation metrics, and statistical analysis.
- Experience with Jupyter notebooks for experimentation and analysis.
- Academic or personal project experience with LLM APIs (OpenAI, Anthropic, Hugging Face).
- Understanding of embeddings, semantic similarity, and vector representations.
- Familiarity with structured output generation (JSON, Pydantic models).
- Exposure to NLP concepts (classification, similarity, clustering).
- Comfortable with Git, APIs, and JSON data structures.
- Basic testing knowledge (pytest or similar).
- Understanding of async programming patterns in Python.
- Basic SQL for data queries and analysis.
Preferred Qualifications
- Research experience in NLP, ML, or AI (thesis, publications, or projects).
- Personal projects with LangChain, LlamaIndex, or custom LLM agents.
- Experience with sentence-transformers, OpenAI embeddings, or similar.
- Familiarity with vector databases (Pinecone, Weaviate, Chroma, pgvector).
- Coursework in NLP, deep learning, or machine learning.
- Understanding of fine-tuning, LoRA, or model adaptation techniques.
- Interest in AI safety, adversarial ML, or red teaming.
- Exposure to experiment tracking tools (MLflow, Weights & Biases).
- Knowledge of graph structures or taxonomy systems.
- Docker/Kubernetes basics (helpful but not required).
Our Commitment
We're trailblazers that dream big, take risks, and challenge cybersecurity's status quo. It's simple: we can't accomplish our mission without diverse teams innovating, together.
We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [Confidential Information].
Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship No. Please note that we will not sponsor applicants for work visas for this position.
