About the Role
Office Beacon is looking for an enthusiastic AI/ML Engineer Junior who is interested in building practical skills in Artificial Intelligence and Machine Learning.
This is an entry-level engineering role designed for candidates with 0–1 year of experience.
The role is well suited to someone with strong Python fundamentals, an understanding of basic AI/ML concepts, and a strong interest in learning how AI-powered applications are developed and evaluated in a production environment.
Key Responsibilities
AI Testing and Evaluation
- Test AI-generated outputs against expected results and source data.
- Compare model responses with source information and expected data structures.
- Identify and document hallucinations, missing information, inconsistent responses, and other AI output issues.
- Support regression testing when AI models, prompts, or workflows are updated.
- Maintain clear records of test results and evaluation findings.
- Assist senior engineers in identifying recurring AI performance issues.
Data Preparation and Annotation
- Prepare datasets used for AI testing and model evaluation.
- Label and organize information from documents, forms, screenshots, images, and structured data.
- Maintain clean and organized test datasets and files.
- Create expected-output examples for testing and validation.
- Assist in maintaining reference datasets used to measure AI accuracy.
- Perform basic data-quality checks before datasets are used for evaluation.
Engineering Support
- Write basic Python scripts for data cleaning, transformation, and JSON validation.
- Perform API testing using tools such as Postman, Swagger, or similar platforms.
- Assist with testing AI APIs and backend services.
- Document experiments, test procedures, results, and technical observations.
- Support senior engineers with basic troubleshooting and issue investigation.
- Follow established coding, testing, documentation, and development practices.
Responsible AI and Data Protection
- Validate AI outputs against source data and expected results.
- Identify and report hallucinations, unsafe outputs, missing fields, and inconsistent responses.
- Use only approved datasets, tools, and testing environments.
- Follow established data-separation and data-protection procedures.
- Maintain appropriate evidence for AI testing and regression testing.
- Protect confidential and sensitive information during testing.
- Escalate significant privacy, security, or quality concerns to senior engineers.
Must-Have Qualifications
- Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field, or currently pursuing such a degree.
- 0–1 year of relevant experience, academic projects, or hands-on technical projects.
- Strong fundamentals in Python programming.
- Basic understanding of Artificial Intelligence and Machine Learning concepts.
- Basic understanding of JSON and REST API concepts.
- Familiarity with Git/version control.
- Basic understanding of data validation and data quality.
- Strong analytical and problem-solving abilities.
- High attention to detail and accuracy.
- Ability to learn new technical concepts and work effectively with senior engineers.
Preferred Qualifications
- Familiarity with Hugging Face or other AI/ML libraries and platforms.
- Experience using Python notebooks such as Jupyter.
- Familiarity with Pandas for basic data processing.
- Exposure to OCR or Document AI concepts.
- Basic experience with Docker.
- Familiarity with AI/ML automation or software development practices.
- Understanding of basic data privacy and responsible AI principles.
- Experience completing academic or personal projects involving AI, ML, NLP, Generative AI, or data processing.