Machine Learning Engineering Intern
Menlo Park
R&D /
Intern /
On-site
We're looking for a passionate ML Engineering intern to help us push the boundaries of what's possible with large language models (LLM). You'll work closely with our ML team. This is an “intern-to-full-time” position with possible conversion into full time employment.
Key responsibilities include:
- Develop Natural Language Processing techniques like retrieval-augmentation, factual corrections, and model calibration to improve model accuracy and reduce hallucinations.
- Build tools and evaluation frameworks to objectively measure model performance, quality and risk. Areas like bias detection, toxicity analysis etc.
- Contribute to our model training pipeline by researching and implementing novel optimization techniques like self-supervised learning and multi-task training.
- Stay on top of the latest advances in representation learning and propose new architectural variants to maximize our models' usefulness while maintaining safety.
- Publish code, papers and tutorials to disseminate your work and help fellow researchers.
- You'll be working at the forefront of ML, with top engineers. Expect to learn cutting-edge techniques and apply them to real-world problems at an ambitious startup.
Requirements:
- Background in ML/NLP with strong Python skills
- Deep learning experience with frameworks like TensorFlow/PyTorch
- Passion for AI safety, ethics and oversight
- Research mindset to continuously push boundaries
- Ability to clearly communicate technical work
- Enrolled in a relevant Master's/PhD program
This is a 2-4+ month full-time paid internship. Please apply with a resume, projects, publications, and cover letter.
