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

Innodata is expanding its team of technical experts in LLM training, post-training, and evaluation systems. As an AI/ML Research Engineer, LLM Training & Evaluation, you will build and optimize the technical foundations that power model improvement for foundation model builders and leading labs.

Requirements

• BS/MS/PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or a related quantitative technical field (MS/PhD preferred)
• 2-3 years of relevant industry or research engineering experience in ML/AI systems
• Hands-on experience with LLM training / fine-tuning / post-training, including at least one of:
• Strong programming skills in Python and experience building production-quality ML code
• Experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow) and model libraries/tooling (e.g., Hugging Face ecosystem, vLLM, distributed training stacks)
• Experience designing and implementing evaluation pipelines for LLM/ML systems, including metrics computation, dataset handling, and experiment comparisons
• Strong understanding of data pipelines and ML systems engineering, including reproducibility, observability, and debugging
• Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data engineers, and customer technical leads
• Strong written and verbal communication skills, including the ability to explain complex technical tradeoffs to both technical and non-technical audiences

Benefits

• 401k Matching