- Company Name
- Censys
- Job Title
- 2026 AI/ML Engineering Intern, Platform
- Job Description
-
**Job Title**
AI/ML Software Engineering Intern, Platform
**Role Summary**
A 12‑week internship focused on applying machine learning, automation, and generative AI to enhance a cybersecurity platform’s data visualization, search, recommendation, and reporting capabilities. The intern will collaborate with senior engineers, contribute code to production systems, and prototype AI‑driven product features.
**Expectations**
- Demonstrate initiative and deliver tangible project outcomes within the internship timeline.
- Work effectively in a fast‑moving, remote‑first environment and attend required on‑site onboarding and wrap‑up weeks.
- Communicate progress, challenges, and ideas clearly with the engineering team and stakeholders.
- Follow engineering best practices (version control, testing, code reviews).
**Key Responsibilities**
- Develop AI‑powered visualisation recommendations (e.g., auto‑select chart types).
- Integrate AI‑driven search suggestions and contextual understanding into the platform.
- Build recommendation engines for queries, insights, and automated report summaries.
- Create explainability tools and dashboards to visualize model behavior and results.
- Prototype and pitch independent AI/ML ideas aligned with product goals.
- Write clean, modular Python code for data processing, model training, and inference pipelines.
- Collaborate on API and microservice integration of ML features; assist with containerization (Docker) as needed.
**Required Skills**
- Proficient in Python with experience in libraries such as PyTorch, TensorFlow, Scikit‑Learn, Pandas, NumPy.
- Strong grasp of machine‑learning fundamentals (supervised/unsupervised learning, feature engineering, evaluation metrics).
- Exposure to NLP or generative AI techniques (LLMs, embeddings, transformers).
- Experience handling large datasets and performing data cleaning, normalization, and sampling.
- Familiarity with data‑visualization tools (Matplotlib, Seaborn, Plotly, Vega‑Lite) and building interactive dashboards.
- Competent with Git/GitHub, unit testing, and code review workflows.
- Basic understanding of APIs, microservices, and optional knowledge of Docker or cloud platforms (AWS/GCP/Azure).
- Interest in cybersecurity or related domain concepts is a plus.
**Required Education & Certifications**
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related quantitative field.
- Relevant coursework or projects in machine learning, artificial intelligence, data analytics, or software engineering.
- No formal certifications required; demonstrated technical proficiency through academic work or personal projects is sufficient.