Innodata Inc.
Technology
PromptEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Prompt Engineer at Innodata Inc.. Skills: Prompt engineering, LLMs, Data annotation, AI/ML. Design prompt strategies. Implement prompt strategies”
What You'll Achieve.
Improve accuracy; Improve localization; Improve cultural alignment; Ensure high standards of quality; Ensure high standards of reliability; Deliver high-quality outputs
Industry & Context.
Iterate on solutions; Optimize prompt design; Assess model reliability; Assess model bias; Assess model generalizability
What They're Looking For.
Must Have
2 years of prompt engineering, 2 years of LLM fine-tuning, 2 years of AI/ML roles, Experience designing data annotation workflows, Experience automating data annotation workflows, Demonstrated experience programmatically using LLMs, Expertise in Python for NLU, Expertise in Python for data processing, Expertise in Python for statistical analysis, Experience with data pipelines, Experience with automation tools, Experience integrating models into production systems
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Design prompt strategies
Implement prompt strategies
Improve cultural alignment
Translate business requirements
Develop prompt-based workflows
Ensure high standards of quality
Ensure high standards of reliability
Collaborate with data scientists
Collaborate with linguists
Collaborate with localization experts
Ensure cultural relevance
Understand software stack components
Optimize prompt design
Analyze model performance
Ensure AI models meet acceptance criteria
Deliver high-quality outputs
Communicate technical findings
Communicate solution strategies
Present model performance
Present actionable insights
Collaborate on data pipelines
Collaborate on workflows
Integrate LLMs into automated systems
Enhance efficiency of data annotation
Enhance effectiveness of data annotation
Create guidelines for prompt usage
Create training materials for prompt usage
Stay informed on industry trends
Stay informed on industry tools
Enhance prompt engineering techniques
How You'll Work.
Team & Collaboration
With Product; With Data Science; With Operations; With client stakeholders; With data scientists; With linguists; With localization experts
Communication Scope
Technical findings; Solution strategies; Model performance; Actionable insights
Full Job Description
Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Innodata is building a team of Prompt Engineers to leverage large language models (LLMs) to automate and optimize data annotation and human evaluation workflows. In this role, you will design and implement effective prompt strategies that improve accuracy, localization, and cultural alignment in data labeling and translation processes. Working closely with Product, Data Science, Operations, and client stakeholders, you will translate business requirements into scalable AI-driven solutions. You will identify automation opportunities, develop prompt-based workflows, and continuously measure and refine performance to ensure high standards of quality and reliability. This position offers the opportunity to directly impact efficiency, scalability and innovation for a leading global technology partner. What You’ll Own: Collaborate with data scientists, linguists, and localization experts to ensure accuracy and cultural relevance. Prototype and validate AI models to demonstrate initial feasibility, potential impact, and overall effectiveness. Design, develop, and implement prompts for data labeling and localization processes within software applications. Understand the current components of the software stack, use cases and problems and iterate on solutions leveraging a solid knowledge of data structures, data formats, and data modeling. Conduct user testing and feedback
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