Machine Translation Researcher (NMT & LLMs)

Job Title: Machine Translation Researcher (NMT & LLMs)

Location: Fully Remote India

Reports To: VP of AI

Employment Type: Full-time

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About the Role

We are looking for a highly experienced Machine Translation Researcher to join our team and drive innovation in Neural Machine Translation (NMT) and LLM-based translation systems. This is a fully remote, long-term position, allowing you to live and work from anywhere while collaborating with a global team.

In this role, you will design, train, and deploy state-of-the-art machine translation models, work with large-scale multilingual datasets, and integrate advanced LLM-based translation and RAG pipelines into production workflows. You will also help push the boundaries of translation quality, particularly for low-resource languages and domain-adapted MT systems.

This position is ideal for researchers who combine strong theoretical understanding of modern NLP architectures with hands-on experience building and deploying large-scale MT systems.

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Key Responsibilities:

Machine Translation Research & Development

Design, train, fine-tune, and evaluate Neural Machine Translation (NMT) models across multiple language pairs (both high- and low-resource languages).

Develop state-of-the-art Transformer-based encoderdecoder models for production translation systems.

Conduct research and experimentation in areas such as:

o Domain Adaptation

o Knowledge Distillation

o Factored MT

o Adaptive NMT

o Low-resource MT with LLM augmentation

Improve model robustness, generalization, and domain specialization.

LLM-Based Translation Systems

Fine-tune and adapt large language models for translation tasks, including:

o Qwen

o DeepSeek

o LLaMA

Apply LoRA / QLoRA and other parameter-efficient fine-tuning methods for multilingual MT tasks.

Build RAG-based translation pipelines using domain-specific knowledge sources.

Design prompting strategies and translation prompting frameworks for LLM-assisted translation workflows.

Architecture & Modeling

Design and implement custom Transformer architectures and enhancements such as:

o Additional Quality Estimation (QE) heads

o Multi-stage LLM chaining pipelines

o Hybrid NMT + LLM translation systems

Experiment with scalable architectures for multilingual and low-resource language translation.

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Required Qualifications

Education

Bachelor's or Master's degree in one of the following: Computational Linguistics, Language Technology, Computer Science, Artificial Intelligence or a related field with equivalent experience.

Core Experience

Minimum 5 years of research experience in Machine Translation or NLP.

Expert knowledge of Neural Machine Translation architectures, especially Transformer-based encoderdecoder models.

Strong experience in training and evaluating NMT models at scale.

Proven expertise in domain adaptation and fine-tuning of translation models.

Hands-on experience with LLM fine-tuning for translation tasks.

Programming & ML Skills

Strong programming skills in Python.

Experience with deep learning frameworks such as: PyTorch, TensorFlow, MXNet

Experience with MT/NLP toolkits such as: Fairseq, Marian, Sockeye, OpenNMT

LLM & Advanced NLP Experience

Practical experience fine-tuning LLMs for translation, including: Qwen, DeepSeek, LLaMA

Expertise with LoRA / QLoRA and parameter-efficient fine-tuning methods.

Experience designing RAG pipelines for translation or multilingual NLP tasks.

Advanced knowledge of prompt engineering for translation workflows.

Research & Publications

Published research in top NLP or MT conferences, such as: ACL, AMTA, EAMT, EACL, ACL, WMT or similar venues

Systems & Deployment

Experience designing large-scale MT inference systems.

Experience building data pipelines and training corpora for NMT models.

Experience developing REST APIs for ML services.

Soft Skills

Excellent communication and documentation skills.

Ability to collaborate with cross-functional teams and translate research into production systems.