(Senior or Staff) Machine Learning Engineer
Gretel Labs - San Diego, CA
posted 4 days ago
About the position
Our Applied Science team is looking (in the U.S. or Canada) for a Machine Learning Engineer who is passionate about building software that developers love. At Gretel, we're building the platform that developers and data scientists trust for safe, AI-ready data. Our platform combines differential privacy with state-of-the-art AI to generate synthetic data across multiple modalities, whether starting from your own unique data or creating entirely new datasets from prompts. We enable organizations to unlock sensitive data for AI development and analytics. We believe you shouldn't have to search for the right dataset, you should be able to generate exactly what you need while maintaining the highest standards of privacy and utility. We're a highly collaborative remote-first company with employees across the US & Canada. Our innovative and transparent culture offers employees the autonomy, tools, and trust to act like owners. We're disrupting how organizations innovate with data and are looking for a talented Machine Learning Engineer to join our mission!
Responsibilities
- Design and implement the software behind our core product.
- Collaborate with applied scientists, engineers, and product managers to unlock real-world use cases for synthetic data generation.
- Help develop models that can better detect heart disease across genders and ethnicities.
- Contribute to financial models that can better respond to unseen data and market changes.
- Create safe datasets that enable medical researchers to share data on rare diseases without compromising patient identity.
Requirements
- 5+ years of professional experience in software development, ideally with an ML specialization.
- Significant experience working with tools from Python's ML ecosystem.
- Strong foundation in deep learning and related mathematics.
- Demonstrated experience working on complex software projects and a track record of delivering technical excellence.
Nice-to-haves
- Experience working remotely in a distributed company.
- Experience developing large-scale models and deploying them into production.
- Experience working with LLM evaluations, agentic workflows, and/or information-retrieval / RAG systems.
Benefits
- Employee compensation will be determined based on interview performance, level of experience, specialization of skills, and market rate.
- Salary ranges are updated regularly using premium market data.
- Stock options may represent a significant portion of your compensation.
