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 looking for a Data Delivery Manager to own the execution and delivery of human data solutions for off-the-shelf AI/ML products. This role sits at the intersection of client management and data operations — you'll be the primary driver ensuring projects are delivered on time, to spec, and to the client's satisfaction, while managing competing priorities across internal teams. This is a hands-on, ownership-driven role, — strong execution, client management, and analytical instincts matter the most. What You’ll Own: Take full ownership of assigned client engagements, executing delivery from kickoff through completion Build and manage human data (data annotation, labeling, evaluation datasets) for off-the-shelf AI/ML products Coordinate cross-functional internal teams (data operations, analysts, SMEs) to keep projects on track Understand and translate technical concepts to non-technical stakeholders and vice versa Balance competing priorities across multiple clients/projects, proactively identifying and resolving risks Use quality metrics, acceptance criteria, and dataset-level analysis to identify gaps and drive improvements As bandwidth allows, contribute to process and delivery improvements beyond day-to-day execution You’ll Thrive in This Role If You Have: 4+ years of experience in technical program/project management, delivery management, or data operations within AI/ML, data annotation, or related technology domains Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field Experience working in technical settings (does not require a deeply technical background) Demonstrated ability to manage and influence cross-functional teams without direct authority; potential to build and lead a team as the practice scales Strong attention to detail with a track record of owning client-facing deliverables to exacting specifications Strong analytical skills — comfortable working with quality metrics, acceptance criteria, and dataset-level analysis Excellent client management, communication, and risk management skills Preferred Skills: Understanding of LLMs, model evaluation, benchmarking, data annotation, and AI/ML data production workflows Experience delivering datasets or evaluation assets to AI labs, research organizations, or ML engineering teams Exposure to benchmark/eval frameworks, annotation platforms, SME-driven data production, or RLHF/human-feedback workflows Working knowledge of Python, SQL, or analytics/BI tools for dataset inspection and metrics reporting PMP, Agile, or equivalent program management certification The expected salary range for this position is $140,000 - $150,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at consumer.ftc.gov. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Requirements

Must-haves

Take full ownership of assigned client engagements, executing delivery from kickoff through completion
Build and manage human data (data annotation, labeling, evaluation datasets) for off-the-shelf AI/ML products
Coordinate cross-functional internal teams (data operations, analysts, SMEs) to keep projects on track
Understand and translate technical concepts to non-technical stakeholders and vice versa
Balance competing priorities across multiple clients/projects, proactively identifying and resolving risks
Use quality metrics, acceptance criteria, and dataset-level analysis to identify gaps and drive improvements
As bandwidth allows, contribute to process and delivery improvements beyond day-to-day execution
You’ll Thrive in This Role If You Have:
4+ years of experience in technical program/project management, delivery management, or data operations within AI/ML, data annotation, or related technology domains
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field
Experience working in technical settings (does not require a deeply technical background)
Demonstrated ability to manage and influence cross-functional teams without direct authority; potential to build and lead a team as the practice scales
Strong attention to detail with a track record of owning client-facing deliverables to exacting specifications
Strong analytical skills — comfortable working with quality metrics, acceptance criteria, and dataset-level analysis
Excellent client management, communication, and risk management skills

Nice-to-haves

Understanding of LLMs, model evaluation, benchmarking, data annotation, and AI/ML data production workflows
Experience delivering datasets or evaluation assets to AI labs, research organizations, or ML engineering teams
Exposure to benchmark/eval frameworks, annotation platforms, SME-driven data production, or RLHF/human-feedback workflows
Working knowledge of Python, SQL, or analytics/BI tools for dataset inspection and metrics reporting
PMP, Agile, or equivalent program management certification
If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Application prep

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Keywords to mirror

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