Internship Programs
Career-shaping Internships
Join as an intern and work on technology that’s changing how the world computes. From internships in software and hardware engineering to marketing and research placements, our interns help power AI everywhere. Curiosity drives everything here. You’ll ask questions, experiment by doing, and collaborate with people who challenge and support you to think bigger and go further. Many of our interns return as graduates, because once you’ve shaped what’s next, you’ll want to keep going.
Work on real AI systems used in global e-commerce, contributing to technologies in conversational AI, voice commerce, recommendation systems, and intelligent agents. Gain hands-on experience solving practical challenges while accelerating your technical and research skills.
Collaborate with leading AI researchers, engineers, and product teams working at the intersection of artificial intelligence and commerce. Receive mentorship, feedback, and exposure to real product development and innovation processes.
Turn ideas into impact by contributing to research, experiments, patents, and publications connected to real business needs. Explore how cutting-edge AI moves from academic concepts into scalable, customer-facing products.
Develop valuable skills in AI, machine learning, data analysis, product thinking, and innovation. Whether your goal is academia, industry, or entrepreneurship, gain experience that strengthens your portfolio and career opportunities.
The Hiring Process
Our hiring process is a great opportunity for us to get to know each other. The steps may differ slightly depending on where you are applying, but once you submit your application, one of our recruiters will explain the process and support you throughout.
Apply
Submit your CV and tell us what excites you about the future of AI in commerce. Applications are evaluated based on your skills, curiosity, motivation, and overall fit with the programme. Please submit your application using your official university email address.
Send your email to internships@rezolve.com
Introductory Conversation
A short virtual conversation to get to know you, your interests, experiences, and what you hope to gain from the internship. This is also your chance to learn more about Rezolve AI and our work.
Technical & Problem-Solving Interview
Meet members of the engineering and research team to discuss how you approach problems, think through challenges, and apply technical knowledge to practical scenarios.
Final Interview
Successful candidates receive an offer and join our onboarding process, where you will meet your team, mentor, and begin your journey building AI for global commerce.
All Openings
Commerce Agent Interaction Analyst
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Commerce Agent Interaction Analyst
- Analyse real commerce agent conversations and user journeys
- Identify common queries, behaviours, friction points, and failure patterns
- Produce insights to guide product, evaluation, and model improvement work
- Help define patterns for synthetic data generation and testing scenarios
- MSc / advanced BSc in CS, ML, Data Science, HCI, Linguistics or related
- Strong analytical skills and attention to detail
- Comfortable working with conversational, behavioural, or qualitative data
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Experience analysing real-world AI agent interactions
- Understanding of user behaviour in AI-powered commerce journeys
- Skills in conversation analysis, evaluation design, and data generation
- Direct exposure to how customer data informs agent improvement
Recommendation Intelligence Researcher
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Recommendation Intelligence Researcher
- Analyse product, basket, and interaction signals for recommendation opportunities
- Explore statistical, ML, and rule-based recommendation approaches
- Study recommendation timing across search, chat, basket, and checkout journeys
- Design evaluation methods for relevance, conversion, and customer experience
- MSc / advanced BSc in CS, ML, Data Science, Statistics, Economics or related
- Strong Python and comfort working with behavioural or transaction data
- Interest in recommender systems, ranking, experimentation, or consumer behaviour
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Practical experience with AI-driven commerce recommendations
- Understanding of upsell, cross-sell, and personalisation strategies
- Skills in experimentation, evaluation, and data-driven decisioning
- Exposure to how recommendations affect commercial outcomes
AI Commerce Research Analyst
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
AI Commerce Research Analyst
- Map the global landscape of AI shopping assistants
- Run structured user-journey tests against these assistants
- Identify where each solution breaks: hallucinations, weak product understanding, poor checkout flow, broken multi-turn conversations, missing personalisation
- Benchmark performance on accuracy, intent understanding, conversion friction, latency, and error recovery
- Produce weekly written analyses and a final comparative report
- Curious by default, sceptical by training
- Comfortable writing structured analysis, not just bullet points
- Patient enough to run the same test 30 times to find the pattern
- Bonus: background in retail, UX research, or LLM evaluation
- How agentic commerce works in production at scale
- How to design rigorous evaluation methodologies for LLM-powered systems
- The gap between marketing claims and shipped reality across major retailers
- Direct exposure to frontier platforms (Visa’s Intelligent Commerce Connect, Google’s UCP, OpenAI’s ACP) and how enterprise platforms are responding
Voice AI & Speech Model Evaluator
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Voice AI & Speech Model Evaluator
- Prepare and curate datasets for STT, VAD, TTS, and Omni-LLM model evaluation
- Build benchmarks for denoisers and other voice enhancement components
- Extend datasets across multiple languages and product categories (e.g. fashion, grocery)
- Design evaluation metrics appropriate for voice quality, accuracy, and latency
- Run benchmark evaluations and produce comparison reports to guide model selection
- MSc / advanced BSc in CS, Speech Processing, ML or related
- Familiarity with speech and audio processing (STT, TTS, VAD concepts)
- Strong Python; experience with audio data pipelines a plus
- Detail-oriented: dataset quality is critical in this role.
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Specialist knowledge of voice AI evaluation methodology
- Experience with multilingual and multi-domain dataset preparation
- Exposure to the full voice AI stack from raw audio to deployed models
- Skills applicable to a rapidly growing area of applied AI
Cortex Agent Evaluation & User Journey Analyst
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Cortex Agent Evaluation & User Journey Analyst
- Extend the Brain Testing Tool to evaluate Cortex across merchant categories (response quality, tool usage, latency, failure patterns)
- Collect and classify user journey data to understand how non-developers interact with Cortex
- Identify common workflows, friction points, and gaps between expected and actual behaviour
- Challenge the current conversational agent solution and propose modelling improvements
- Test and evaluate agentic AI solutions; contribute to iterative product improvements
- MSc / advanced BSc in CS, HCI, ML or related
- Experience with conversational or agentic AI systems
- Analytical mindset: comfortable with qualitative and quantitative evaluation
- Curiosity about user behaviour and product design
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- End-to-end experience building and operating AI evaluation infrastructure
- Understanding of agentic AI design patterns and failure modes
- Skills in user research and journey mapping applied to AI products
- Direct product impact: findings feed directly into the Cortex roadmap
AI Search Experimentation Analyst
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
AI Search Experimentation Analyst
- Design and run experiments comparing retrieval and ranking strategies for product search
- Evaluate trade-offs between semantic, hybrid, and keyword-based search approaches
- Collaborate with Brainpowa engineers to test and integrate new search models
- Analyse search quality metrics and distil findings into actionable recommendations
- Document experiments rigorously to build an institutional knowledge base
- MSc / advanced BSc in CS, Information Retrieval, ML or related
- Experience with search systems, embeddings, and vector databases
- Strong Python and data analysis skills
- Collaborative mindset — this role involves close cross-team work
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Deep expertise in e-commerce search and product discovery
- Practical experience with retrieval evaluation and A/B experimentation
- Collaboration skills across research and engineering teams
- Insight into how search quality directly drives business outcomes
Real-Time Context & LLM Optimisation Specialist
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Real-Time Context & LLM Optimisation Specialist
- Research and prototype real-time context injection strategies for LLMs under latency constraints
- Fine-tune domain-specific LLMs tailored to Rezolve’s commerce agents
- Manually label and curate training scenarios – rigorous but foundational work
- Research and report on the latest industry and academic innovations; formalise an ongoing review process
- Contribute to identifying which new models or techniques can improve agent performance
- MSc / advanced BSc in CS, ML or related
- Solid Python and experience with LLM training/fine-tuning workflows
- Attention to detail for data labelling and annotation tasks
- Self-directed: proactively explores new papers and tools
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Hands-on experience with LLM fine-tuning and RLHF/alignment techniques
- Deep understanding of latency-sensitive AI system design
- Skills in dataset creation, annotation, and quality assurance
- Exposure to the full ML development lifecycle in a production environment
Model Benchmarking & Automated Evaluation Analyst
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Model Benchmarking & Automated Evaluation Analyst
- Design benchmarks for retrieval, summarisation, orchestration, and answer-refinement components
- Curate gold-standard evaluation datasets from real product and search data
- Build automated evaluation pipelines covering quality, latency, throughput, and cost
- Analyse results and produce model-selection recommendations with clear trade-offs
- Explore LLM-as-a-judge and other scalable evaluation techniques
- MSc / advanced BSc in CS, ML, Data Science or related
- Strong Python and comfort working with data at scale
- Familiarity with transformers, embeddings, and retrieval-augmented generation
- Interest in evaluation methodology, benchmarking, and metrics design
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Production AI system architecture: multi-model pipelines and real-time inference
- LLM and retrieval evaluation methodology with statistical rigour
- MLOps and CI/CD for automated model evaluation
- Data-driven model selection in a fast-moving landscape
- Exposure to full stack from research to deployment
Empathetic Dialogue & Conversational AI Specialist
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Empathetic Dialogue & Conversational AI Specialist
- Define and measure empathy in AI dialogue; design LLM-as-a-judge evaluation frameworks
- Investigate how empathy metrics correlate with customer experience and conversion
- Design annotation guidelines and build data generation pipelines for empathetic sales conversations
- Fine-tune and prompt LLMs to improve empathetic behaviour
- Monitor trade-offs between empathy, factual accuracy, tool use, and conversion.
- MSc / advanced BSc in CS, ML, Computational Linguistics or related
- Strong Python; familiarity with NLP/LLM frameworks
- Interest in dialogue systems and human-computer interaction
- Comfort reading and synthesising academic papers
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Applied AI research: from literature review to measurable outcomes
- Data-centric AI and evaluation benchmark design
- LLM fine-tuning and alignment techniques
- Multi-objective optimisation in a live product
- Option to publish or present findings
Past Opportunities
Graph Intelligence AI Researcher
- RAIL (Rezolve AI Lab)
- 2–3 months (Jul–Sep) or 6 months rolling
Graph Intelligence AI Researcher
- Model product, attribute, and catalog relationships as graphs
- Explore GraphRAG, graph ML, and graph-based discovery methods
- Prototype visualisations and signals for search, recommendation, and catalog understanding
- Evaluate where graph methods add measurable value
- MSc / advanced BSc in CS, ML, Data Science, Information Retrieval or related
- Strong Python and data analysis skills
- Interest in graphs, embeddings, recommender systems, or knowledge graphs
- AI-native: actively uses Copilot, Cursor, Claude Code, etc.
- Experience applying graph methods to real commerce problems
- Understanding of GraphRAG, knowledge graphs, and graph ML
- Skills in catalog intelligence, visualisation, and applied AI research
- Exposure to search, RAG, and agentic commerce systems