Research Engineer, FlexOlmo
Designs and implements infrastructure for training next-generation LLM architectures focused on Mixture-of-Experts and long-context models. Requires 4+ years building ML pipelines with PyTorch/JAX/TF, deep learning expertise, and strong software engineering skills.
About the job
Responsibilities
- Building infrastructure to facilitate the next generation of LLM research.
- Optimizing training and inference for language models.
- Triaging between experiments and executing on the most impactful.
- Bridging the gap between cutting-edge research and a widely adopted product.
- Bringing software engineering best practices to a research environment.
- Supporting and collaborating with an open-source community.
- Releasing contributions back to the broader community in the form of open source software, model releases, and additions to Ai2's public API and open research datasets, as well as technical reports.
Requirements
- A bachelor's degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP, or a related field, or equivalent relevant experience, and expertise at building ML infrastructure.
- 4+ years of experience building infrastructure that handles data preprocessing/transformation and model training, evaluation, inference, and deployment. Experience in the complete model development cycle, including data set construction, training, tuning, evaluation, performance profiling, and monitoring.
- Knowledge of modern deep learning and natural language processing techniques.
- Strong software engineering skills, particularly around building performant systems and debugging.
- Experience with Python and PyTorch/Jax/Tensorflow as well as feel at ease in picking up new programming languages, libraries, or APIs as project needs evolve.
- Familiarity working with cloud compute resources (e.g. AWS) and containerization (e.g. Docker).
- Strong collaboration and communication skills.
Nice-to-Haves
- Advanced degree in Data Science/CS/EE/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience.
- Contributions to open-source ML or research libraries (e.g. spaCy, AllenNLP, transformers).
- Experience successfully operating models at scale in a production setting.
- Experience in HPC settings.
- Curiosity about AI research.
Compensation
Base salary range: $128,880 - $193,320, plus generous bonus plans.
Skills
PyTorch, JAX, TensorFlow, Python, AWS, Docker, Deep Learning, Natural Language Processing, Transformers, Mixture-Of-Experts, LLMs, Machine Learning Infrastructure
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