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. What You’ll Do

• 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 master’s 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.