Machine Learning Engineer

Join a small growing team building AI-powered tools for hardware development. You will develop custom machine learning models and take them from research and prototyping through production helping translate product needs into useful features.

• Design train and evaluate custom machine learning models and embeddings.
• Own data workflows from curation and preparation through model training.
• Build and improve training and evaluation processes including experiment tracking metrics and reproducibility.
• Deploy models monitor their real-world performance and iterate on them.
• Partner with cross-functional teammates to turn product needs into machine learning solutions.
• Write and review clean Python code and contribute to testing and debugging.
• Follow advances in language models embeddings and representation learning and apply relevant ideas.

• At least 4 years of machine learning engineering experience or equivalent research experience; the role is suited to candidates with roughly 4 to 10 or more years of experience.
• A masters or doctoral degree in machine learning computer science or a related field with substantial machine learning depth.
• Strong Python skills and proficiency with PyTorch or a comparable deep learning framework.
• Experience developing deep learning models and embeddings from the ground up including transformer-based architectures rather than relying only on adapting existing models or integrating third-party APIs.
• Hands-on experience with large language models graph neural networks or graph transformers.
• Experience taking machine learning models into production with a focus on model development product machine learning or research.
• Cloud or ML platform experience backend development and familiarity with CAD geometry robotics or other physical-domain problems are helpful.
• Clear communication strong problem-solving skills and the ability to work effectively in a fast-paced team.

Base salary: $175000 to $250000 annually plus equity. Visa sponsorship is available.

On-site in Los Angeles California.