Principal Software Engineer

Founded in 2019, Pigment stands out as one of the fastest-growing SaaS companies globally, redefining business planning and performance with our AI-powered platform. We empower organizations across diverse industries, including Consumer Packaged Goods, Retail, and Technology, to seamlessly integrate data, people, and processes, enabling them to plan and adapt rapidly. With a vibrant team of over 500 professionals across North America and Europe, and offices in New York, Toronto, London, Paris, and the Bay Area, Pigment has successfully secured nearly $400 million in funding from leading global venture capitalists. Our recognition as a Visionary in the 2024 Gartner® Magic Quadrant™ for Financial Planning Software underscores our commitment to excellence, as we proudly partner with industry leaders like Unilever, Vinci, Kayak, Siemens, and Coca-Cola. At Pigment, we champion smart risks, celebrate bold ideas, and challenge the status quo—all as a united team. Every team member has the opportunity to make a significant impact and tackle ambitious challenges. Together, we pursue excellence with a collaborative spirit, continuously raising the bar to ensure strong performance and a proactive approach while fostering an environment of humility. If you are passionate about innovation and wish to collaborate with some of the brightest minds in the industry, we would love to hear from you! <a href="https://www.pigment.com/" rel="noopener noreferrer" target="_blank" style="background-color: rgb(255, 255, 255); color: rgba(0, 0, 0, 0.87);">https://www.pigment.com/</a>

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Our Engineering teamOur 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 <a href="https://engineering.pigment.com/" class="postings-link" rel="noopener noreferrer">Tech Blog</a>!

<h4>Your mission</h4><ul><li>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.</li><li>Project Overview:</li><li>Exploring Fine-Tuned Open-Source Alternatives to Commercial LLMs</li><li>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.</li><li>As an intern, you will:</li><li>Experiment with fine-tuning techniques such as LoRA, QLoRA, and other Parameter-Efficient Fine-Tuning (PEFT) methods.</li><li>Benchmark model performance, accuracy, and inference latency across a range of tasks.</li><li>Identify and document trade-offs between accuracy, speed, and cost for different fine-tuning and deployment strategies.</li><li>Contribute to the development of a scalable, cost-effective foundation for custom LLM deployment to complement Pigment’s current stack.</li><li>Collaborate with engineers and data scientists to design robust evaluation pipelines and share findings internally.</li><li>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.</li></ul>

<h4>Technical stack</h4><ul><li>Our current AI and engineering stack includes:</li><li>Languages &amp; Frameworks: Python, LangGraph</li><li>Data &amp; ML Infrastructure: Weights &amp; Biases, Hugging Face Hub, Google Cloud Platform (GCP), Docker, Kubernetes</li><li>Databases: PostgreSQL</li><li>CI/CD &amp; Experimentation: CircleCI, MLflow, and internal orchestration tools</li><li>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.</li></ul>

Data Scientist Internship

Pigment

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