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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Ai Squared - **Location:** Washington, DC, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Continuous Integration, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Google Cloud, Feature Engineering, Pytorch, Large Language Models, Generative AI, Kubernetes, Machine Learning Operations, Data Pipelines, Docker, Databricks - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/data-scientist-ai-squared-7278571 ## About the Role * 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. ## Description 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 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? 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