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.
- 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
Company website•Software Development
Enterprises and federal agencies are investing heavily in AI, but deployment repeatedly fails at the “last mile” leading to the loss of trillions of dollars in wasted investment and lost opportunity.
AISquared solves the last mile problem by creating a secure, production-grade way to operationalize AI inside the business applications where work actually happens, without requiring large new engineering lifts, while giving leaders measurable visibility into adoption, performance, and business impact.
AI Squared provides a comprehensive, low-code platform, UNIFI and Sparx, designed to “CLOSE” the gap between AI potential and real operational outcomes through five core capabilities:
1. Connects by integrating virtually any data source and any AI model using pre-built connectors.
2. Learns by capturing real-time user feedback directly inside the workflow to support continuous model improvement.
3. Orchestrates by managing complex data workflows and policies through a single UI.
4. Secures deployments with defense-grade controls.
5. Embeds insights where work happens by delivering no-code widgets and visualizations or AI chatbots integrated directly into systems.
This results in 5x faster time-to-value and measurable ROI that is Trusted by leading financial institutions, complex supply chain organizations, and the United States Department of Defense, AI Squared helps organizations move from stalled pilots to real adoption, faster decision making, and measurable operational impact.
Learn more at https://aisquared.ai/
Request a demo at https://aisquared.ai/request-demo/