Data Scientist

<div class="p-rich_text_section"><strong data-stringify-type="bold">Data Scientist</strong></div> <div class="p-rich_text_section"><strong data-stringify-type="bold">Washington, DC (Hybrid)</strong></div> <div class="p-rich_text_section"> </div> <div class="p-rich_text_section"><strong data-stringify-type="bold">About the Role:</strong></div> <div class="p-rich_text_section"><br>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.</div> <div class="p-rich_text_section"><br><strong data-stringify-type="bold">Key Responsibilities:</strong></div> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="0" data-border="0"> <li data-stringify-indent="0" data-stringify-border="0">Leverage 5+ years of experience in data science to design, implement, and optimize machine learning models and pipelines.</li> <li data-stringify-indent="0" data-stringify-border="0">Develop, fine-tune, and evaluate large language models (LLMs) for a variety of applications, ensuring accuracy, performance, and robustness.</li> <li data-stringify-indent="0" data-stringify-border="0">Collaborate with engineering and product teams to integrate AI/ML solutions into our platform in a scalable and maintainable way.</li> <li data-stringify-indent="0" data-stringify-border="0">Conduct applied research, staying current on advances in LLMs, generative AI, and data science methodologies, and translate them into practical solutions.</li> <li data-stringify-indent="0" data-stringify-border="0">Build end-to-end workflows, from data exploration and feature engineering to training, validation, deployment, and monitoring in production.</li> <li data-stringify-indent="0" data-stringify-border="0">Apply modern containerization and orchestration techniques (e.g., Docker, Kubernetes) to support reproducible experimentation and deployment.</li> <li data-stringify-indent="0" data-stringify-border="0">Work with cloud platforms (e.g., Databricks, AWS, GCP, Azure) to manage data pipelines, large-scale training jobs, and distributed systems.</li> <li data-stringify-indent="0" data-stringify-border="0">Collaborate across teams to ensure our AI capabilities align with platform goals and business needs.</li> </ul> <div class="p-rich_text_section"><strong data-stringify-type="bold">Qualifications:</strong></div> <ul class="p-rich_text_list p-rich_text_list__bullet p-rich_text_list--nested" data-stringify-type="unordered-list" data-list-tree="true" data-indent="0" data-border="0"> <li data-stringify-indent="0" data-stringify-border="0">5+ years of experience as a Data Scientist or Machine Learning Engineer, with proven success in deploying models to production.</li> <li data-stringify-indent="0" data-stringify-border="0">Hands-on experience with large language models (LLMs); fine-tuning experience strongly preferred.</li> <li data-stringify-indent="0" data-stringify-border="0">Strong background in Python and ML frameworks such as PyTorch or TensorFlow.</li> <li data-stringify-indent="0" data-stringify-border="0">Proficiency in containerization and orchestration technologies (Docker, Kubernetes).</li> <li data-stringify-indent="0" data-stringify-border="0">