> Markdown version of [/jobs/ext/1265377-data-scientist-ia-generativa](https://www.wearedevelopers.com/jobs/ext/1265377-data-scientist-ia-generativa). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Scientist IA Generativa

- **Company:** Transcat, Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Continuous Integration, Dataspaces, Python (Programming Language), NumPy, Prometheus, Swagger, Openapi, Flask (Web Framework), Large Language Models, Grafana, Fastapi, Pandas, Matplotlib, Scikit Learn, Kubernetes, Information Technology, Api Design, GPT, Docker
- **Published:** July 14, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p4j7pmwz4k

## About the Role

* A solid track record in IT projects (around 7 years or more) and several of them focused on data and artificial intelligence.
 * At least 5 years participating in analysis, design and development of systems that work with large volumes of information or AI solutions.
 * Complete confidence in Python and its data ecosystem: pandas, numpy, scikit-learn, visualization with matplotlib/seaborn and intensive use of notebooks.
 * Real-world experience building APIs and services around models (FastAPI/Flask, OpenAPI/Swagger, CI/CD, Docker, Kubernetes).
 * Several projects under your belt with generative AI : RAG architectures, GPT-type models, LLaMa or Mistral, Transformers, fine-tuning, embeddings and metrics to evaluate LLMs.

## Description

Instead of being in a data tower, you'll work very closely with development and architecture, from idea to deployment.

 * You will design RAG-based generative AI solutions: deciding how the index is built, what context is retrieved, and how the LLM call is orchestrated.
 * You will prepare and understand the data (structured and unstructured), defining the transformations they need to feed the generative models.
 * You will test, compare and adjust large models (GPT, LLaMa, Mistral), defining prompt strategies, fine-tuning and continuous evaluation.
 * You will work hand in hand with the Python team to expose your models through robust, monitored APIs deployed in cloud-native environments.
 * You will measure the impact of what you do: quality of responses, times, user feedback, and opportunities for improvement.

Beyond Meeting Minimum Requirements, We Will Focus On

 * Real-world cases where you have used generative AI to solve specific problems (not just PoCs that remained in a repo).
 * How do you combine your technical profile with the ability to explain decisions and results to non-technical people?
 * Additional experience moving comfortably between containers, Kubernetes, observability (Grafana, Prometheus) and vector databases.


## Related Videos

- [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps)
- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast)
- [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension)
- [Supercharge your cloud-native applications with Generative AI](https://www.wearedevelopers.com/videos/950-supercharge-your-cloud-native-applications-with-generative-ai)
- [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker)

## Related Articles

- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [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)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [The State of WebDev AI 2025 Results: What Can We Learn?](https://www.wearedevelopers.com/magazine/581-the-state-of-webdev-ai-2025-results-what-can-we-learn)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)