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Who we are:Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider-of-choice to 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of clean and optimized digital data to all industries.
Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.
Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany.
We’re poised for a period of explosive growth over the next few years. Position Summary:Innodata is building a team of Language Data Scientists and Gen AI experts to help our customers advance GenAI applications.
You will work hands-on with multi-modal and multi-lingual datasets and collaborate with cross-functional partners.
You will use your experience with human and synthetic data workflows to drive innovation and continuous improvement.
The ideal candidate must have the right mix of skills in (computational) linguistics and human evaluation tasks, data science, and data engineering.
Who We’re Looking For: You have at least 5 years of relevant experience with data creation, curation, and analysis for GenAI applications (e. g. RAG, Agents, complex reasoning).
You are experienced driving long term projects where you set the strategic plan towards success, using your knowledge of AI, data science, and process design excellence.
You are an expert at working cross functionally with both technical and non-technical stakeholders. Despite ambiguity, you use your technical knowledge and experience of working with multiple stake holder to drive solutions.
You bring a research-oriented mindset towards developing long-term excellence.
You are an expert in designing collection, evaluation and quality assurance processes, using human-in-the-loop and synthetic techniques.
You bring a wealth of expertise in language, culture, and multi-lingual projects.
You are experienced in analyzing data with advanced statistical tools and driving success through process excellence.
Your understanding of machine learning, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) help you tackle challenges with a critical, innovative mindset. Tell Me More:As a Senior Language Data Scientist, you lead projects and own processes for creating, validating and annotating data for use in LLM/ML applications.
This can be natural language data or multimodal data including images, video, audio, and others.
You consult and engage with customers to understand their business goals and design processes to meet them.
You generate insights about the client’s processes and products to drive improvement and innovation.
You advise and support business unit heads on engaging with customers to understand the upstream activities that would be performed using Innodata Inc services. Responsibilities:You can lead long-term projects with high complexity and ambiguity from first discussion with the client to completionDesign/improve workflows to create data for AI/ML training and evaluation.
Includes human annotation and data-collection workflows, as well as synthetic onesDive deep into existing workflows and processes to gather data and insights, make recommendations, and drive improvement through innovation and cross-functional collaboration with customers Critically assess annotation tooling and workflowsQuantitatively analyze large datasets, perform statistical analysis, calculate metrics, and make recommendations to improve accuracy and performance Work closely with client stakeholders on understanding goals, gathering
requirements
, proposing solutions, and executing them. Set an ambitious research agenda for improving our products and servicesContribute to establishing best practices and standards for generative AI development with customers and within the organization
Requirements
MA in (computational) linguistics, data science, computer science (AI / ML / NLU), quantitative social sciences or a related scientific / quantitative field, PhD strongly preferredAbility to collaborate directly with technical stakeholders including senior project managers, data engineers, and research scientists. Collaborating with cross-functional teams to define AI project
requirements
and objectives, ensuring alignment with overall business goalsDesign efficient data strategies for complex long-term projects, potentially involving multiple teams and workflows. Knowledge of how components of GenAI products or services combine to workDeveloping clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non
Technical
stakeholdersFamiliarity with GenAI technologies that enables you to improve existing processes to handle future challenges. Language and language data expertise: Extensive experience working with human language data and designing human evaluation tasks, including multi-phase and complex workflows. Deep understanding of language and its relationship with cultureAbility to identify ambiguity and subjectivity in languageAbility to work with multi-lingual and multi-modal projectsQuantitative Analysis Skills: Advanced knowledge of statistics, metrics (e. g. f1 score, inter-rater reliability metrics), and data analysis methods such as sampling. Technical skills: Experience with Natural Language Processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. o Proficiency in Python tohandle / transform large datasets (e. g. pre- and postprocessing data, pandas) perform quantitative analysesvisualize data (for example matplotlib, seaborn) Data processing:Deep understanding of data pipelines to support ML and NLP workflows, § Knowledge of efficient data collection, transformation, and storage Knowledge of data structures, algorithms, and data engineering principlesExcellent interpersonal skills for effective cross-functional stakeholder engagementExcellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutionsAbility to work independently and collaborate as part of a teamAdaptable to changing technologies and methodologiesAbility to translate experience, research and development information to understand client products and services. Providing technical mentorship and guidance to junior team membersPreferred SkillsConducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques · Knowledge of optimizing existing generative AI models for improved performance, scalability, and efficiency Experience of developing and maintaining ML/AI pipelines, including data preprocessing, feature extraction, model training, and evaluation · Model Fine-Tuning: Knowledge of Fine-tuning pre-trained models to adapt them to specific tasks and datasets, improving their performance and relevanceUnderstanding of techniques such as GPT, VAE, and GANsPlease 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 https://consumer. ftc. gov/articles/job-scams.
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.
Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.
Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany.
We’re poised for a period of explosive growth over the next few years. Position Summary:Innodata is building a team of Language Data Scientists and Gen AI experts to help our customers advance GenAI applications.
You will work hands-on with multi-modal and multi-lingual datasets and collaborate with cross-functional partners.
You will use your experience with human and synthetic data workflows to drive innovation and continuous improvement.
The ideal candidate must have the right mix of skills in (computational) linguistics and human evaluation tasks, data science, and data engineering.
Who We’re Looking For: You have at least 5 years of relevant experience with data creation, curation, and analysis for GenAI applications (e. g. RAG, Agents, complex reasoning).
You are experienced driving long term projects where you set the strategic plan towards success, using your knowledge of AI, data science, and process design excellence.
You are an expert at working cross functionally with both technical and non-technical stakeholders. Despite ambiguity, you use your technical knowledge and experience of working with multiple stake holder to drive solutions.
You bring a research-oriented mindset towards developing long-term excellence.
You are an expert in designing collection, evaluation and quality assurance processes, using human-in-the-loop and synthetic techniques.
You bring a wealth of expertise in language, culture, and multi-lingual projects.
You are experienced in analyzing data with advanced statistical tools and driving success through process excellence.
Your understanding of machine learning, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) help you tackle challenges with a critical, innovative mindset. Tell Me More:As a Senior Language Data Scientist, you lead projects and own processes for creating, validating and annotating data for use in LLM/ML applications.
This can be natural language data or multimodal data including images, video, audio, and others.
You consult and engage with customers to understand their business goals and design processes to meet them.
You generate insights about the client’s processes and products to drive improvement and innovation.
You advise and support business unit heads on engaging with customers to understand the upstream activities that would be performed using Innodata Inc services. Responsibilities:You can lead long-term projects with high complexity and ambiguity from first discussion with the client to completionDesign/improve workflows to create data for AI/ML training and evaluation.
Includes human annotation and data-collection workflows, as well as synthetic onesDive deep into existing workflows and processes to gather data and insights, make recommendations, and drive improvement through innovation and cross-functional collaboration with customers Critically assess annotation tooling and workflowsQuantitatively analyze large datasets, perform statistical analysis, calculate metrics, and make recommendations to improve accuracy and performance Work closely with client stakeholders on understanding goals, gathering
requirements
, proposing solutions, and executing them. Set an ambitious research agenda for improving our products and servicesContribute to establishing best practices and standards for generative AI development with customers and within the organization
Requirements
MA in (computational) linguistics, data science, computer science (AI / ML / NLU), quantitative social sciences or a related scientific / quantitative field, PhD strongly preferredAbility to collaborate directly with technical stakeholders including senior project managers, data engineers, and research scientists. Collaborating with cross-functional teams to define AI project
requirements
and objectives, ensuring alignment with overall business goalsDesign efficient data strategies for complex long-term projects, potentially involving multiple teams and workflows. Knowledge of how components of GenAI products or services combine to workDeveloping clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non
Technical
stakeholdersFamiliarity with GenAI technologies that enables you to improve existing processes to handle future challenges. Language and language data expertise: Extensive experience working with human language data and designing human evaluation tasks, including multi-phase and complex workflows. Deep understanding of language and its relationship with cultureAbility to identify ambiguity and subjectivity in languageAbility to work with multi-lingual and multi-modal projectsQuantitative Analysis Skills: Advanced knowledge of statistics, metrics (e. g. f1 score, inter-rater reliability metrics), and data analysis methods such as sampling. Technical skills: Experience with Natural Language Processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. o Proficiency in Python tohandle / transform large datasets (e. g. pre- and postprocessing data, pandas) perform quantitative analysesvisualize data (for example matplotlib, seaborn) Data processing:Deep understanding of data pipelines to support ML and NLP workflows, § Knowledge of efficient data collection, transformation, and storage Knowledge of data structures, algorithms, and data engineering principlesExcellent interpersonal skills for effective cross-functional stakeholder engagementExcellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutionsAbility to work independently and collaborate as part of a teamAdaptable to changing technologies and methodologiesAbility to translate experience, research and development information to understand client products and services. Providing technical mentorship and guidance to junior team membersPreferred SkillsConducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques · Knowledge of optimizing existing generative AI models for improved performance, scalability, and efficiency Experience of developing and maintaining ML/AI pipelines, including data preprocessing, feature extraction, model training, and evaluation · Model Fine-Tuning: Knowledge of Fine-tuning pre-trained models to adapt them to specific tasks and datasets, improving their performance and relevanceUnderstanding of techniques such as GPT, VAE, and GANsPlease 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 https://consumer. ftc. gov/articles/job-scams.
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.
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