Prompt Engineer - LLM Automation

@ Innodata Inc

About the Role

Innodata is building a team of prompt engineers to harness the power of LLMs to automate data annotation and human evaluation workflows. The goal is to facilitate accurate, localized, and culturally adapted data labeling and translation processes through effective prompt design and implementation. You will work directly with a leading technology company to identify opportunities for automation, design solutions, and drive measurable improvements.

You will collaborate with product managers, data scientists, and client teams to solve complex problems, reduce human effort, and ensure that AI-driven processes meet high standards for quality and reliability. Your work enhances data annotation and evaluation processes to help our client scale efficiently.

Key Responsibilities

• Collaborate with data scientists, linguists, and localization experts for accuracy and cultural relevance.
• Prototype and validate AI models and demonstrate feasibility.
• Design, develop, and implement prompts for labeling and localization.
• Iterate on solutions using knowledge of data structures, formats, and modeling.
• Conduct user testing and feedback analysis for optimal prompt design.
• Analyze model performance with KPIs to meet customer criteria.
• Communicate technical findings to both technical and non-technical stakeholders.
• Collaborate on data pipelines and workflows integrating LLMs into automation systems.
• Create guidelines and training materials for prompt usage.
• Stay informed on industry trends and tools in data labeling and localization.

Technical & Required Skills

• Deep understanding of LLMs (e.g., transformer-based architectures).
• Experience using LLMs to automate data labeling, classification, and localization tasks.
• Strong expertise in Python, with knowledge of JSON, Javascript or XML.
• Familiarity with TensorFlow, PyTorch, Jupyter, and other AI/ML tools.
• Experience with APIs and platforms like OpenAI and Hugging Face.
• Knowledge of localization best practices and cultural nuances.
• Understanding of LLM evaluation metrics and model reliability.
• Experience with data pipelines, automation tools, and production model integration.
• Collaborative mindset and ability to work independently.
• Attention to detail in delivering high-quality AI solutions.
• Appreciation for Diversity, Equity, and Inclusion in AI.

Preferred Skills and Experience

• 2 years of prompt engineering or related AI/ML roles.
• Familiarity with annotation tools/platforms such as Labelbox.
• Experience designing and automating data annotation workflows.
• Familiarity with cloud platforms, containerization, and model deployment.
• Knowledge of additional languages.

Minimum Education Requirements

Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Linguistics, Localization or a related field.

Key skills/competency

• LLMs
• Automation
• Data Annotation
• Localization
• Python
• AI/ML
• Prompt Design
• Evaluation Metrics
• Data Pipelines
• Collaboration