Senior AI Scientist

About Pigment

Pigment is a cutting-edge AI-driven business planning and performance management platform designed to enhance agility and scalability. It unifies people, data, and processes into a single sophisticated platform, empowering diverse teams including Finance and HR to create, adapt, and synchronize strategic plans in real time. Founded in 2019, Pigment has rapidly established itself among the leading SaaS companies globally, serving notable clients such as Unilever, Snowflake, Siemens, and DPD. The company has expanded its team to over 600 members across Paris, London, New York, Toronto, San Francisco, and Austin, has secured nearly $400M from premier investors, and was recognized as a Visionary in the 2024 Gartner® Magic Quadrant™ for Financial Planning Software.

Job Role and Responsibilities

• Develop AI-driven features integrated with the Pigment computation engine, ensuring determinism, auditability, and data visualization capabilities.
• Contribute to AI functionalities that have a strong product vision, real-world application, and are built for long-term sustainability.
• Engage in programming within a production-grade Python codebase, transitioning experimental concepts to production-ready features.
• Design and execute experiments for benchmarking and evaluating the efficacy of different models and AI architectures.
• Maintain awareness of emerging research and advancements in agentic architectures, natural language processing, and large language models, integrating innovative methods to enhance platform features.

Candidate Requirements

• Possess a Master’s degree or Ph.D. in Computer Science, Mathematics, or a closely related discipline.
• Proficient in Python programming and familiar with machine learning and generative AI frameworks such as Langchain, Langgraph, TensorFlow, PyTorch, and scikit-learn.
• Experienced in assessing pre-trained AI models as well as fine-tuning and training models.
• Knowledgeable in recent developments of agentic architectures.
• Strong analytical problem-solving ability with a capacity to work autonomously.
• Excellent communication skills to convey complex mathematical and AI concepts effectively to interdisciplinary teams involving research, engineering, and product personnel.
• Previous involvement in building and deploying complex products leveraging large language models (LLMs).
• Expertise in LLM-based or deep learning-driven tabular data interpretation, schema inference, or table representation learning techniques including TAPAS, TaBERT, TURL, and similar Omniparser approaches.
• Familiarity with contemporary deep learning forecasting models such as TimesFM, Chronos, and TOTO, or equivalent foundational time series prediction models.

Benefits and Perks

• Competitive compensation package and stock options granting stake in Pigment’s future growth.
• Comprehensive health insurance coverage through Alan Blue for employees and their families at no cost.
• Weekly lunch provisions and lunch vouchers via Swile card providing flexible meal options.
• Subscription to Egym Wellpass (formerly Gymlib), granting access to gyms, studios, and wellness facilities across France.
• Flexible and trusting work hours supporting remote-friendly engagement.
• Annual company offsite events and modern offices situated in major cities including New York, San Francisco, Toronto, Paris, and London.
• Access to high-quality hardware and equipment subject to availability to optimize work conditions.

Additional Information

Pigment performs lawful background screenings during the recruitment process which may include employment verification, educational credential checks, and criminal record evaluations where permitted. All background checks are conducted with candidate consent and maintain confidentiality. The company is an equal opportunity employer valuing diversity, inclusion, and equality without discrimination based on age, gender identity, ethnicity, disability, sexual orientation, or other protected characteristics. Pigment utilizes AI-assisted tools to support application review but final hiring decisions remain human-led. Queries regarding data privacy during hiring can be directed to their contacts.