Machine Learning Engineer
Scaled Cognition is developing a new generation of rational, controllable AI models deployable as domain experts for grounded, real-world applications.
As a Machine Learning Engineer (MLE) at Scaled Cognition you will:
- Build and maintain the end-to-end infrastructure, pipelines, and tooling for our AI models.
- Work closely with research scientists and product engineers to enable rapid iteration and experimentation from ideation to production.
Example projects could include:
- Working with optimization libraries to scale training of large AI models across thousands of GPUs.
- Refining ML pipelines to 100x existing capacity for constrained pieces such as training data, model size, or compute parallelization.
- Optimizing data collection and preparation techniques to produce higher quality training datasets.
You might be the right person for the job if you:
- Enjoy scaling up models and software processes.
- Are eager to learn and have an optimistic mindset.
- Excel in collaborative, cross-functional team settings.
- Experience with relevant frameworks such as PyTorch, TensorFlow, or JAX.
- Experience with modern machine learning pipelining techniques and platforms.
- Experience optimizing end to end processes in secure, highly reliable environments.