AI Researcher Resume Keywords 2026
Use these specific keywords in your resume to help you pass Applicant Tracking Systems (ATS) and catch the attention of recruiters hiring for AI Researcher roles.
Hard Skills
- Machine learning
- Deep learning
- Reinforcement learning
- Natural language processing (NLP)
- Computer vision
- Probabilistic modeling
- Bayesian inference
- Optimization algorithms
- Representation learning
- Generative models (GANs, VAEs)
- Time series modeling
- Causal inference
- Large language models (LLMs)
- Foundation models
Technical Proficiencies
- Python
- PyTorch
- TensorFlow
- JAX
- NumPy / SciPy
- scikit-learn
- Hugging Face Transformers
- CUDA / GPU acceleration
- Distributed training
- Experiment tracking (MLflow, Weights & Biases)
- Linux / Unix
- Git / version control
- Cloud platforms (AWS, GCP, Azure)
- Docker / containerization
Research & Analytical Skills
- Algorithm development
- Mathematical modeling
- Statistical analysis
- Theoretical analysis
- Experimental design
- A/B testing
- Benchmarking and evaluation
- Reading and synthesizing academic literature
- Paper writing and publication
- Conference presentations
Domain & Industry Skills
- Applied AI research
- Product-focused research
- Model deployment collaboration
- AI safety and alignment
- Responsible AI / ethical AI
- Data privacy and security awareness
- Cross-functional collaboration with engineering
Soft Skills
- Problem solving
- Critical thinking
- Hypothesis-driven research
- Scientific communication
- Technical writing
- Collaboration and teamwork
- Mentoring and supervision
- Stakeholder communication
- Project management
Action Verbs
- Researched
- Developed
- Designed
- Implemented
- Prototyped
- Optimized
- Evaluated
- Benchmarked
- Published
- Presented
- Collaborated
- Mentored
Pro Tip
Don't just list these keywords! Weave them naturally into your Professional Summary and Work Experience bullet points to show how you used these skills to achieve results.
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