Build, deploy, and govern AI inside the systems your teams already use. Zero trust security, agentic workflows, and enterprise-grade governance. Backed by NEA.
About the role
We are looking for a highly motivated Data Scientist with a strong background in applied machine learning and AI to join our growing team. In this role, you will be a key contributor to the development of core AI/ML solutions that power our platform. You will collaborate closely with product and engineering teams, applying state-of-the-art techniques to solve complex challenges, advance our use of large language models (LLMs), and ensure scalable, production-ready solutions.
What they're looking for
- 5+ years of experience as a Data Scientist or Machine Learning Engineer, with proven success in deploying models to production
- Hands-on experience with large language models (LLMs), fine-tuning experience strongly preferred
- Strong background in Python and ML frameworks such as PyTorch or TensorFlow
- Proficiency in containerization and orchestration technologies (Docker, Kubernetes)
- Experience with cloud platforms and ML ecosystems (Databricks, AWS, GCP, Azure)
- Familiarity with MLOps best practices, including model deployment, monitoring, and CI/CD for ML
More about this role
Data Scientist
Washington, DC (Hybrid)
We are looking for a highly motivated Data Scientist with a strong background in applied machine learning and AI to join our growing team. In this role, you will be a key contributor to the development of core AI/ML solutions that power our platform. You will collaborate closely with product and engineering teams, applying state-of-the-art techniques to solve complex challenges, advance our use of large language models (LLMs), and ensure scalable, production-ready solutions.
- Leverage 5+ years of experience in data science to design, implement, and optimize machine learning models and pipelines.
- Develop, fine-tune, and evaluate large language models (LLMs) for a variety of applications, ensuring accuracy, performance, and robustness.
- Collaborate with engineering and product teams to integrate AI/ML solutions into our platform in a scalable and maintainable way.
- Conduct applied research, staying current on advances in LLMs, generative AI, and data science methodologies, and translate them into practical solutions.
- Build end-to-end workflows, from data exploration and feature engineering to training, validation, deployment, and...
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