Gen AI Engineer
CA$80k - CA$90k • Remote • Remote - Canada • Full-time
Posted 23d ago
Job Location
Remote - Canada
Tech Stack
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
AI Engineer
About the job
Innodata is seeking Prompt Engineers to leverage large language models (LLMs) for automating and optimizing data annotation and human evaluation workflows. In this role, you will design and implement effective prompt strategies to enhance accuracy, localization, and cultural alignment in data labeling and translation processes. You will collaborate with product, data science, operations, and client stakeholders to translate business requirements into scalable AI-driven solutions, identify automation opportunities, develop prompt-based workflows, and continuously measure and refine performance. This position offers the opportunity to directly impact efficiency, scalability, and innovation for a leading global technology partner.
Responsibilities
- Collaborate with data scientists, linguists, and localization experts to ensure accuracy and cultural relevance.
- Prototype and validate AI models to demonstrate feasibility, potential impact, and effectiveness.
- Design, develop, and implement prompts for data labeling and localization processes within software applications.
- Understand software stack components, use cases, and problems, iterating on solutions with knowledge of data structures, formats, and modeling.
- Conduct user testing and feedback analysis to optimize prompt design for data accuracy and linguistic consistency.
- Analyze model performance using KPIs and metrics to ensure AI models meet customer acceptance criteria.
- Communicate technical findings and solution strategies to both technical and non-technical stakeholders.
- Collaborate on data pipelines and workflows that integrate LLMs into automated systems.
- Create guidelines and training materials for prompt usage in data labeling and localization projects.
- Stay informed on data labeling and localization industry trends and tools to enhance prompt engineering techniques.
Requirements
- 2 years of prompt engineering, LLM fine-tuning, or related AI/ML roles.
- Familiarity with tools/platforms for annotation and human-in-the-loop workflows (e.g., Labelbox).
- Experience designing and automating data annotation workflows.
- Knowledge of data annotation and challenges of scaling human-in-the-loop workflows.
- Familiarity with cloud platforms, containerization, and model deployment.
- Deep understanding of LLMs (e.g., transformer-based architectures).
- Demonstrated experience programmatically using LLMs to automate data labeling, classification, localization, and annotation tasks.
- Strong expertise in Python for NLU, data processing, and statistical analysis.
- Familiarity with JSON, Javascript, or XML.
- Experience with popular frameworks and libraries like TensorFlow, PyTorch, and Jupyter.
- Familiarity with APIs and platforms for working with LLMs (e.g., OpenAI, Hugging Face).
- Knowledge of localization best practices and cultural nuances.
- Strong understanding of LLM evaluation metrics and ability to assess model reliability, bias, and generalizability.
- Experience working with data pipelines, automation tools, and integrating models into production systems.