• Support the development and integration of AI/ML models, LLM integrations, or intelligent services into controlled or production-like systems under guidance
• Assist with data collection, preprocessing, transformation, and management for model training, testing, validation, and evaluation
• Contribute to testing, debugging, and improving AI-enabled solutions for performance, reliability, explainability, and maintainability
• Support model training workflows, inference endpoints, prompt-based interactions, evaluation routines, data retrieval pipelines, AI agents, and agentic workflows
• Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions
• Document model parameters, prompts, evaluation assumptions, data pipelines, system integrations, and technical decisions
• Participate in Agile practices including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies
• Help ensure AI systems align with enterprise expectations for reliability, safety, governance, security, and compliance
• Develop foundational experience with APIs, cloud environments, data platforms, CI/CD, containers, deployment patterns, and monitoring
• Learn how AI-enabled software and machine learning solutions are designed, built, tested, and delivered in an enterprise environment
Requirements
- Currently enrolled in a Master’s degree program in Computer Science, Machine Learning, Data Science, Computer Engineering, or another technical field
- Knowledge of Python and foundational data processing technologies
- Foundational understanding of computer science concepts, including data structures, algorithms, debugging, testing, and problem solving
- Understanding of machine learning concepts such as model training, evaluation, feature engineering, and experimentation
- Experience using modern AI systems such as LLM APIs, prompt-based interactions, retrieval patterns, or generative AI applications
- Awareness of responsible AI, security, governance, compliance, and reliability considerations
- Strong communication, collaboration, documentation, and learning agility with the ability to work effectively in a team environment
- Preferred experience through academic coursework, research, projects, open-source contributions, internships, or extracurricular activities using Python, R, Java, JavaScript, or similar technologies
- Preferred familiarity with NLP techniques, embeddings, BERT, transformers, APIs, data pipelines, ETL, cloud environments, containerized development, CI/CD, version control, testing, and code reviews
- Preferred experience with AI-powered applications, LLM integrations, prompt engineering, retrieval-augmented generation, AI agents, agentic workflows, ML algorithms, and practical AI/ML problems
- Familiarity with cybersecurity and AI security concepts, including secure software development, application security, identity and access management, data protection, encryption, secure API design, threat modeling, prompt injection, data leakage, and model abuse
Core Competencies
Demonstrates foundational experience in AI/ML model development, data processing, and integration within enterprise environments. Proficient in Python and familiar with modern AI systems, cloud technologies, and Agile practices.
Highest-signal resume keywords
- Python Programming
- Machine Learning Concepts
- AI/ML Model Training
- Data Processing Technologies
- Agile Methodologies
ATS Optimization Keywords
Hard Skills
- Data Structures
- Algorithms
- Debugging
- Testing
- Feature Engineering
- NLP Techniques
- ETL
- CI/CD
- Version Control
- AI Algorithms
Soft Skills
- Communication
- Collaboration
- Documentation
- Learning Agility
- Teamwork
Industry Keywords
- Responsible AI
- Security
- Governance
- Compliance
- Reliability
- Cybersecurity
- Application Security
- Data Protection
- Encryption
- Threat Modeling
Tools & Technologies
- APIs
- Cloud Environments
- Data Platforms
- Containers
- Monitoring Tools
- LLM APIs
- Generative AI Applications
- Retrieval Patterns
- Prompt Engineering
- Agentic Workflows
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Undergraduate AI Engineer, Internship Programme employer: Jobtailor
As a Client Services Coordinator at our dynamic company, you will thrive in a supportive work culture that prioritises employee growth and development. We offer comprehensive training, opportunities for advancement, and a collaborative environment where your contributions are valued. Located in a vibrant area, our team enjoys a healthy work-life balance and the chance to engage with diverse clients, making every day rewarding and meaningful.
