Senior Staff Software Engineer (AI Model LifeCycle)

Join Crusoe Energy, a leading company in the AI space. As a Senior Staff Software Engineer, you will play a crucial role in building a comprehensive managed platform for the entire application development lifecycle, with a specific focus on leveraging Machine Learning models. You will manage fine-tuning systems for large foundation models, implement and maintain end-to-end training pipelines for Large Language Models, and oversee dataset, model, and experiment management. This position offers comprehensive health benefits, paid time off, a 401(k) matching program, and resources for mental wellness.

• Concevoir et mettre en œuvre une plateforme gérée pour l'ensemble du cycle de développement des applications, en mettant l'accent sur l'exploitation des modèles d'apprentissage automatique.
• Gérer les systèmes de fine-tuning pour les grands modèles de base, y compris l'orchestration multi-nœuds, le checkpointing, la récupération après échec et l'évolutivité.
• Mettre en œuvre et maintenir des pipelines d'entraînement de bout en bout pour les grands modèles de langage, y compris l'apprentissage par renforcement et la distillation.

• We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services
• If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe
• 8+ years of industry experience leading and driving impactful projects in the AI Space
• Passion for building cutting-edge AI products and solving challenging technical problems
• Hands-on experience training, fine-tuning, and aligning LLMs using Reinforcement Learning and Reinforcement Fine-Tuning (RFT) techniques
• Proactive and collaborative approach with the ability to work autonomously
• Experience in Generative AI (Large Language Models, Multimodal)
• Advanced degree in Computer Science, Engineering, or a related field
• Performance optimizations on GPU systems and inference frameworks
• Contributions to open-source AI projects such as vLLM or similar frameworks
• Proficiency in Golang or Python for large-scale, production-level services and PyTorch