Gen AI Engnineer
Innodata Inc.16 hours ago
Remote, CanadaMid Level
Responsibilities
- Collaborate with data scientists, linguists, localization experts, product teams, operations, and clients to develop accurate and culturally relevant AI solutions.
- Prototype and validate AI models to assess feasibility, impact, and effectiveness.
- Design, develop, and implement prompts for data labeling, annotation, translation, and localization applications.
- Analyze software components, use cases, data structures, data formats, and data models to iterate on scalable solutions.
- Conduct user testing and feedback analysis to improve prompt accuracy and linguistic consistency.
- Measure model performance using KPIs and evaluation metrics, including reliability, bias, and generalizability.
- Integrate LLMs into data pipelines and automated production workflows.
- Communicate technical findings, model performance, and solution strategies to technical and non-technical stakeholders.
- Create prompt usage guidelines and training materials for data labeling and localization projects.
- Monitor industry trends and tools related to data labeling, localization, and prompt engineering.
Requirements
- At least 2 years of prompt engineering, LLM fine-tuning, or related AI/ML experience.
- Experience designing and automating data annotation and human-in-the-loop workflows, including familiarity with tools such as Labelbox.
- Familiarity with cloud platforms, containerization, and model deployment.
- Deep understanding of LLMs, including transformer-based architectures.
- Demonstrated ability to programmatically use LLMs for data labeling, classification, localization, and annotation tasks.
- Strong Python expertise for natural language understanding, data processing, transformation, and statistical analysis.
- Familiarity with JSON, JavaScript, or XML.
- Experience with TensorFlow, PyTorch, Jupyter, and other AI/ML tools.
- Familiarity with LLM APIs and platforms such as OpenAI and Hugging Face.
- Knowledge of localization best practices and cultural nuances across languages and regions.
- Understanding of LLM evaluation metrics and model reliability, bias, and generalizability.
- Experience with data pipelines, automation tools, and integrating models into production systems.
Tech Stack
Categories
About Innodata Inc.
Innodata Inc. builds data engineering and annotation services and platforms that supply training data, evaluation, and pipelines for enterprises and technology companies building AI models, including generative and robotics applications. Its business model centers on B2B services, managed data operations, and tools for data collection, cleansing, and labeling across text, image, video, and sensor data. Founded in 1988 and headquartered in Ridgefield Park, New Jersey, it is a public company trading on NASDAQ (INOD).