01Requirements
MS/PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, AI, or a related quantitative scientific field (PhD strongly preferred)
5+ years of relevant experience in applied research / research science in ML/AI, with substantial work in LLMs or foundation models
Demonstrated experience with LLM evaluation, benchmarking, alignment, post-training, or model quality research
Strong foundation in experimental design, statistical analysis, and scientific reasoning for ML systems
Strong coding skills in Python for research experimentation and analysis (e.g., data processing, evaluation pipelines, statistical analysis, visualization)
Experience working with modern ML tooling/frameworks (e.g., PyTorch, Hugging Face, JAX/TensorFlow as applicable)
Ability to evaluate and compare human and automated evaluation methods, including tradeoffs in cost, reliability, validity, and scalability
Experience designing evaluation studies and protocols that are reproducible across datasets, model versions, and evaluation runs
Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data scientists, and customer technical counterparts
Strong communication skills and ability to present nuanced technical conclusions, assumptions, and limitations clearly.
Benefits:
Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development opportunities
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Company : Innodata Inc.
Salary : Work from home .
