Innodata Inc.

Technology

PromptEngineer

CA$80–85k Canada
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“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.

Technology
Problems you'll solve

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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