Data Scientist Internship
il y a 2 semaines
Our Engineering team
Our Engineering team is responsible for developing our SaaS platform and building a comprehensive and user-friendly product. Pigment engineers participate in the entire application development lifecycle, focusing on design, coding, and keeping the production platform up and running. They can be specialized, but there is no strict separation between infrastructure, backend, and frontend.
We value user-centricity and pragmatism: we choose the most relevant tools for the problem we have to solve, understanding the strengths and constraints of each technology. Our engineering culture also values curiosity, humility, trust, ownership, and team spirit.
Curious to see what we're building? Check out our Tech Blog
Your mission- As a Data Scientist Intern, you will contribute to advancing Pigment's use of Large Language Models (LLMs) by helping us explore how open-source alternatives can complement or replace commercial APIs. You'll work closely with our AI engineering and data science teams to design, fine-tune, and evaluate models that improve both efficiency and performance across our product.
- Project Overview:
- Exploring Fine-Tuned Open-Source Alternatives to Commercial LLMs
- This project investigates replacing select calls to commercial large language models with fine-tuned open-source alternatives. The goal is to develop localized models that deliver similar or improved performance while reducing latency and cost.
- As an intern, you will:
- Experiment with fine-tuning techniques such as LoRA, QLoRA, and other Parameter-Efficient Fine-Tuning (PEFT) methods.
- Benchmark model performance, accuracy, and inference latency across a range of tasks.
- Identify and document trade-offs between accuracy, speed, and cost for different fine-tuning and deployment strategies.
- Contribute to the development of a scalable, cost-effective foundation for custom LLM deployment to complement Pigment's current stack.
- Collaborate with engineers and data scientists to design robust evaluation pipelines and share findings internally.
- You'll gain hands-on experience in modern LLM fine-tuning, LangChain-based orchestration, and MLOps for model deployment, contributing to research with a direct impact on how AI is embedded into Pigment's platform.
- Our current AI and engineering stack includes:
- Languages & Frameworks: Python, LangGraph
- Data & ML Infrastructure: Weights & Biases, Hugging Face Hub, Google Cloud Platform (GCP), Docker, Kubernetes
- Databases: PostgreSQL
- CI/CD & Experimentation: CircleCI, MLflow, and internal orchestration tools
- We don't expect you to know them all. What matters most is your ability to learn quickly, experiment rigorously, and translate data insights into actionable results.
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