Senior AI Translation Engineer (NLP)

About the role

This role focuses on advancing Smartcat's AI-powered translation platform. The work involves developing and refining benchmarks for various translation challenges, and contributing to systems for named entity recognition, word alignment, and automated translation quality assessment. A key aspect is translating product features into quantifiable user use cases to guide development.

The Senior AI Translation Engineer will be responsible for managing end-to-end dataset pipelines, ensuring data quality and flow. This includes understanding and applying text normalization techniques for machine translation and search, as well as core matching approaches. The role also requires operating external large language model providers from end-to-end.

Success in this position means contributing to a platform that helps companies create, translate, and localize global content efficiently. The engineer will also set up infrastructure for self-hosted solutions and write lightweight services with integrated logging and monitoring. This work directly supports Smartcat's goal of scaling its operations significantly within the $100 billion multilingual content industry.

The annual salary for this position is listed between $80,000 and $130,000 USD.

Skills that matter here

• Python: This is the primary language for developing and improving machine learning models and services.
• PyTorch: This framework will be used for building and training deep learning models, particularly for natural language processing tasks.
• Transformers: Experience with Transformer models is essential for working on advanced machine translation and NLP problems.
• MongoDB: This database will likely be used for storing and managing data related to translation models and pipelines.
• Amazon AWS: Knowledge of AWS is important for deploying and managing cloud-based infrastructure and services.
• Prometheus: This tool will be used for monitoring the performance and health of services and infrastructure.

Who this role suits

• A person who can translate abstract product features into concrete, measurable technical tasks.
• Someone who thrives on owning the entire lifecycle of data pipelines, from ingestion to deployment.
• An individual with a deep understanding of machine translation and natural language processing concepts.
• A professional who values working in a fully remote, globally distributed team environment.

From the employer

• Develop and improve benchmarks for translation problems
• Work with NER, word alignment, and automatic translation quality scoring systems
• Set up infrastructure for self-hosted solutions

• Translate product features into measurable user use cases
• Own end-to-end dataset pipelines
• Understand MT/search text normalization and core matching approaches
• Operate external LLM providers end-to-end
• Write lightweight services/jobs with structured logs and monitoring

• Fully remote team
• Be part of an AI Native Organization
• Innovate in a $100 Billion industry
• Join the rocketship to scale-up 10x and beyond