About the Role :

We are seeking a Senior Data Engineer to serve as a technical force multiplier for our Language Engineering team.

You will architect and build the tooling, automation frameworks, and end-to-end evaluation systems that enable our team to thoroughly and efficiently assess conversational AI capabilities built by our engineering teams.

This role combines deep technical expertise in data engineering with specialized knowledge of language technologies and AI/ML systems.

Your work will directly impact how we measure success and drive improvements in our AI systems.

Key Responsibilities :

- Collaborate with computational linguists, AI/ML researchers, and product teams to translate research requirements into scalable technical solutions

- Design and implement automated benchmarking infrastructure for conversational AI evaluation across a range of features, modalities, and languages

- Create intuitive tooling, APIs, and basic frontend interfaces (e.g., internal dashboards) that enable team members to easily configure, execute, and analyse complex benchmarking scenarios

- Establish automated reporting and visualization capabilities that make evaluation results accessible to stakeholders

- Build and implement robust data storage solutions supporting diverse language data types (text, speech, structured annotations) across multiple locales

- Champion automation-first practices while mentoring team members on tooling, code quality, and engineering standards

Required Qualifications :

- Bachelor's degree in Computer Science, Data Science, Computational Linguistics, Human Language Technology, or a related field

- 3+ years of experience building software tooling, data pipelines and evaluation systems

- Advanced Python skills with expertise in data management, analysis, and visualization libraries (pandas, NumPy, matplotlib, plotly)

- Hands-on expertise architecting CI/CD pipelines, managing Git workflows, and deploying AWS infrastructure.

- Demonstrated experience owning technical projects end-to-end.

- Comfortable working in a fast paced, highly collaborative, dynamic work environment.

Preferred Background :

- MS or Advanced degree in Computer Science, Data Science, Computational Linguistics, Human Language Technology, or a related field

- Professional experience in NLP and data science

- Understanding of LLM fundamentals (tokenization, context windows, model behavior including reasoning, factual accuracy, and response quality evaluation)

- Familiarity with quantitative evaluation metrics and standardized benchmarking frameworks for language models

- Strong understanding of scalable system design and APIs with experience contributing to technical architecture decisions

- Experience developing simple web-based dashboards (e.g., using React or Python-based frameworks) is a plus

- Enthusiasm for fostering supportive team dynamics in a global, multicultural environment