Senior AI Engineer
Role details
Job location
Tech stack
Job description
As a Senior AI Engineer at Supermodular AI, you will take ownership of the AI/ML domain, shaping how intelligence is designed, trained, evaluated, and deployed across our products. You'll work with large language models (LLMs), embeddings, retrieval systems, classifiers, and other ML techniques to power the AI agents that our enterprise customers rely on. You will be responsible for both experimentation and productionization: designing robust pipelines for model training, building evaluation frameworks, and ensuring models are reliable, performant, and aligned with customer needs. You'll collaborate with our engineering leads on architectural decisions, while also working with product teams to translate complex AI capabilities into real-world business outcomes. This is a role for someone who thrives on end-to-end ownership of AI systems-balancing research with pragmatic engineering, and mentoring junior colleagues to raise the bar of our AI practice.
Requirements
Do you have a Bachelor's degree?, * Proven experience working with modern AI/ML techniques, including large language models (LLMs), embeddings, retrieval systems, evaluation methods, and classifiers.
- Hands-on expertise in at least one major ML/AI framework (e.g., PyTorch, TensorFlow, JAX) and proficiency with Python for prototyping and production code.
- Strong understanding of evaluation strategies for AI systems, including quantitative metrics and qualitative analysis, to ensure performance and reliability.
- Practical knowledge of key concepts in applied ML, such as prompt engineering, fine-tuning, RAG (retrieval-augmented generation), and supervised/unsupervised learning.
- Experience building and deploying machine learning systems at scale, including data pipelines, model serving, and monitoring.
- Ability to make architectural decisions that balance experimentation, scalability, and maintainability.
- Experience mentoring and collaborating with more junior AI/ML engineers, fostering best practices in research and development.
- Strong communication and collaboration skills to work cross-functionally with engineering, product, and business stakeholders.
- Founder mindset - makes informed decisions with cost/speed/value in mind and is comfortable navigating uncertainty or less-than-clear requirements.