Generative AI Engineer for Enterprise Translation

Apertera; Karachi Division; On-site; PKR 1,800,000 - 3,000,000; Full time

Job summary

Apertera is seeking a Generative AI Engineer to develop our next-generation translation and GenAI service engine. You will work at the intersection of LLM engineering, machine translation, and cloud infrastructure, reporting to the AI Innovation team lead.

You will prototype state-of-the-art algorithms, collaborate with software and DevOps teams, and push the boundaries of GenAI in translation contexts while ensuring production readiness and reproducibility.

Qualifications

• Bachelor's degree in Computer Science, AI, ML or related field; master's preferred.
• 2+ years of industry experience developing GenAI and LLM applications is preferred.
• Strong Python software development skills and production-grade experience.
• Experience with context engineering, RAG, harness engineering is a plus.
• Hands-on experience with PyTorch/TensorFlow and HuggingFace APIs.

Responsibilities

• Implement state-of-the-art LLM techniques including continued pre-training and instruction fine-tuning.
• Collaborate with ML/data engineers to design, build and test models.
• Develop scalable training and inference algorithms for generative models.
• Train and evaluate models with appropriate metrics and benchmarks.
• Prototype end-to-end solutions and deploy GenAI models with DevOps collaboration.

Skills

Python programming

LLM engineering

Deep learning

Education

Bachelor's degree in CS/AI

Master's degree preferred

Tools

PyTorch

TensorFlow

HuggingFace

AWS/GCP/Azure

Job description

Apertera is seeking a Generative AI Engineer to develop our next-generation translation and GenAI service engine. You will work at the intersection of LLM engineering, machine translation, and cloud infrastructure, reporting to the AI Innovation team lead.

You will prototype state-of-the-art algorithms, collaborate with software and DevOps teams, and push the boundaries of GenAI in translation contexts while ensuring production readiness and reproducibility.