AI Sqaured

Integrates AI models into business apps

Data Scientist

Data ScienceConfirmed live in the last 24 hours

Full-timeWashington, DC, USANo salary listedHybrid

About the Job

Requirements

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)
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

Responsibilities

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

Desired Qualifications

Fine-tuning experience with large language models (LLMs) strongly preferred

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.

About the Company

AI Sqaured

Integrates AI models into business apps

Squared.ai builds AI-powered solutions for businesses by integrating predictive and generative AI into business applications. It prepares foundational models and large language models and connects them in real time to mission-critical apps, with intuitive UX so end users can access AI insights without long development cycles. It differentiates itself by focusing on end-to-end deployment, real-time performance monitoring, auto-tuning, and feedback loops to maintain accuracy and adoption across teams, bridging data science with business units. Its goal is to democratize AI-driven decision-making by delivering deployable AI capabilities that boost adoption and enable faster AI-powered decision making in existing workflows.

Company size: 51-200
Company stage: Series A
Total funding: $19.8M
Headquarters: Washington DC, District of Columbia
Founded: 2021

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