Generative AI Engineer

About this task

Responsibilities
- Develop an intelligent translation and related-services engine using generative AI and large language models, from rapid prototyping through collaboration on deployment.
- Implement LLM techniques including continued pre-training, instruction fine-tuning, preference alignment and deployment.
- Work with machine learning and data engineers to design, build and test models. Develop scalable training and inference algorithms using frameworks such as TensorFlow or PyTorch and optimize performance across hardware platforms.
- Train and evaluate generative models against appropriate metrics and benchmarks; tune parameters, architectures and hyperparameters for performance, stability and generalization.
- Build production-ready end-to-end prototypes, collaborate with software and DevOps engineers on deployment, and document code, algorithms and experiments for reproducibility and knowledge sharing.

Requirements
- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning or a related field; a master's degree is preferred.
- Python proficiency and experience building and maintaining scalable, production-grade software. At least two years of industry experience developing GenAI and LLM applications is preferred.
- Project-based experience with context engineering, RAG and harness engineering. LLM post-training, APO or agentic workflows are a plus.
- Hands-on experience with Hugging Face APIs or Amazon Bedrock; strong skills in PyTorch, TensorFlow, Pandas and related Python tools; experience with AWS, GCP or Azure.
- Strong problem-solving, communication, organization and time-management skills, with the ability to work independently and across teams as priorities change.