[Remote] AI/ML Research Engineer, LLM Post-Training & Evaluation

Innodata Inc. is seeking an AI/ML Research Engineer to build and optimize technical foundations for large language model improvement, focusing on post-training and evaluation systems. The role involves designing LLM training pipelines, implementing evaluation systems, and collaborating with research scientists. Ideal candidates have 2-3 years of ML engineering experience and hands-on experience with LLM fine-tuning and modern ML frameworks.

• Lead or co-lead technically complex ML engineering projects from customer discussions through delivery
• Design, build, and improve LLM training and post-training pipelines including data ingestion, fine-tuning, evaluation, and experiment tracking
• Implement and optimize evaluation systems for LLMs and multimodal models, including offline benchmarks and test harnesses
• Integrate human-in-the-loop and AI-augmented evaluation signals into model development workflows
• Build robust infrastructure for reproducible experimentation, metrics logging, and regression monitoring
• Diagnose model behavior and pipeline failures including data issues, training instability, and evaluation drift
• Collaborate with data scientists and research scientists to translate evaluation frameworks into executable systems
• Contribute to internal research and platform development for benchmark frameworks and post-training workflows