Data Scientist Job at Ai Squared, Washington DC

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  • Ai Squared
  • Washington DC

Job Description

Data Scientist

Washington, DC (Hybrid)

 

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.


Key Responsibilities:


  • 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 monitoring in production.

  • Apply modern containerization and orchestration techniques (e.g., Docker, Kubernetes) to support reproducible experimentation and deployment.

  • Work with cloud platforms (e.g., Databricks, AWS, GCP, Azure) to manage data pipelines, large-scale training jobs, and distributed systems.

  • Collaborate across teams to ensure our AI capabilities align with platform goals and business needs.

Qualifications:


  • 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.

  • Strong analytical and problem-solving skills, with the ability to translate research into production-ready solutions.

  • Excellent communication and collaboration skills, with the ability to work effectively across product, engineering, and leadership teams.

  • A proactive, self-starter mindset with a passion for applied research and innovation.

Job Tags

Full time,

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