If you are actively searching for AI internships that go beyond basic model training or surface-level experimentation, Lexsi.ai is offering a highly research-focused AI Research Internship designed for candidates who want to work on alignment, interpretability, and safety of advanced AI systems. This opportunity is ideal for students and early professionals looking for AI internships with real-world research impact, strong mentorship, and exposure to frontier AI problems.
Lexsi Labs (Lexsi.ai) is a frontier AI research lab working on aligned, interpretable, and safe superintelligence. Unlike many AI internships that focus mainly on applications, this role places interns at the core of AI research and tooling, contributing directly to methodologies and open-source libraries used by researchers and engineers.
Internship Overview
| Detail | Information |
|---|---|
| Role | AI Research Intern |
| Company | Lexsi.ai (Lexsi Labs) |
| Internship Type | Full-Time |
| Duration | 6 Months |
| Work Mode | Remote |
| Location Tag | Mumbai (Remote) |
| Start Date | Rolling |
| Conversion Opportunity | Possible full-time offer |
| Primary Focus | Alignment, Interpretability, Safety, Foundation Models |
This is one of the few AI internships where interns work full-time on research problems while being embedded in a fast-moving startup environment that values experimentation, speed, and scientific rigor.
About Lexsi.ai
Lexsi.ai is focused on building transparent, interpretable, and aligned AI systems. The company works on developing new methodologies for model alignment, uncertainty estimation, explainability, and tabular foundational models. These efforts are aimed at helping organizations deploy AI responsibly while maintaining trust and safety.
For candidates exploring AI internships with strong research exposure, Lexsi.ai offers a flat organizational structure where interns contribute directly to meaningful outcomes instead of being limited to support tasks.
What You Will Work On
Interns are assigned to one or more research tracks based on interest and strengths. This makes the internship flexible while still maintaining depth, a feature missing in many AI internships.
Core research areas include:
- Library Development
- Build and improve open-source Python tooling
- Focus on alignment, explainability, robustness, and machine unlearning
- Write clean, modular, and well-documented code
- Explainability & Trust
- Work with XAI techniques such as SHAP, LRP, Grad-CAM, DLB, and Backtrace
- Apply explainability across text, image, and tabular data
- Identify new insights into model decision-making
- Mechanistic Interpretability
- Analyze internal model representations
- Use activation patching and feature visualization
- Diagnose failure modes and emergent behaviors
- Uncertainty & Risk Modeling
- Implement Bayesian methods, ensembles, and test-time augmentation
- Benchmark robustness and uncertainty metrics
- Improve reliability of foundation models
- Tabular Foundational Models
- Work with the Orion team on advanced tabular architectures
- Contribute to open-source libraries like TabTune
- Experiment with new model designs
- Reinforcement Learning
- Explore RL algorithms and fine-tuning strategies
- Contribute to internal RL libraries for alignment
- Research Contributions
- Run structured experiments
- Maintain reproducible experiment code
- Co-author whitepapers or conference submissions
These responsibilities make this one of the most research-intensive AI internships currently available.
Required Qualifications
Candidates applying for these AI internships should meet the following requirements:
- Strong Python programming skills
- Experience writing clean, modular, testable code
- Solid understanding of machine learning and deep learning fundamentals
- Hands-on experience with PyTorch
- Strong understanding of transformer architectures (GPT, BERT, LLaMA, T5, etc.)
- Familiarity with Git, version control, and collaborative development
- Good communication and teamwork skills
Preferred Skills (Any One Is Sufficient)
Having experience in any of the following areas will strengthen your profile for this AI internships role:
- Explainability methods (SHAP, LIME, Grad-CAM, LRP, etc.)
- Mechanistic interpretability and circuit analysis
- Uncertainty estimation and robustness testing
- Model compression (quantization, pruning)
- LLM alignment techniques (RLHF, prompt engineering)
- Tabular foundational models (Orion, TabPFN, TabICL)
- Fine-tuning techniques (LoRA, adapters, instruction tuning)
Nice-to-Have Experience
While not mandatory, the following add value:
- Research publications or preprints
- Open-source AI/ML contributions
- Experience in finance, healthcare, or other risk-sensitive domains
- Familiarity with large-scale training infrastructure
Compared to many AI internships, Lexsi.ai values demonstrated curiosity and hands-on experimentation more than formal credentials alone.
What Lexsi.ai Offers
- Competitive stipend for the internship duration
- Access to GPUs, cloud credits, and proprietary models
- Real-world research impact in high-stakes AI systems
- Opportunity for full-time conversion
- Co-authorship on papers and technical reports
- Exposure to startup + research hybrid culture
These benefits make this role stand out among current AI internships, especially for candidates aiming for research-driven careers.
Who Should Apply
This opportunity is best suited for candidates who:
- Are actively looking for AI internships with real research depth
- Enjoy solving open-ended technical problems
- Want to work on AI safety, interpretability, and alignment
- Prefer ownership-driven environments over rigid hierarchies
- Are comfortable working independently and collaboratively
Final Thoughts
Among the growing number of AI internships, Lexsi.ai’s AI Research Internship offers a rare combination of deep research exposure, strong engineering practices, and real-world relevance. If your goal is to build a strong foundation in advanced AI research while contributing to meaningful outcomes, this is one of the most valuable AI internships you can apply for today.
