Lead LLM Architect & Generative AI Systems

You must have deep technical experience working with methods and technologies related to Large Language Models (LLMs), from model fine-tune to prompt engineering. A strong background developing machine learning background is preferred, in addition to experience building LLMs applications and research. You will enable core models that will be the foundational of the product portfolio & tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work. Opportunity: Machine learning experts on our team can utilize applied science and software development skills to help tweak Foundation Models that help us address some of the hardest problems towards our vision in making insights from complex Industrial data simple & easy to access. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning, AI, and Industrial data architects making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better. This position offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of saving lives with Industrial Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the Industrial domain. Join us and make a significant impact on the future of Industrial DataOps. What You'll Do Lead the system design, architectural strategy on multiple applied research projects that involve a broad set of stakeholders. Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity. Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. Collaborate on modeling techniques to support the full spectrum of LLM tuning including prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF), parameter-efficient tuning, and fine-tuning. Collaborate with stakeholders of LLMs and scope new research and product engagement opportunities. Bring state-of-the-art generative AI systems to Cognite and improve LLM efficiency. Stay up to date on new research and chart the path forward to quality-driven production. Who You Are Extensive software engineering experience in building high performance, large-scale ML systems (Preferably 7 to 10 years of industry experience in the relevant fields).Strong communication skills and the ability to work effectively in a collaborative research environment. Demonstrated leadership abilities, with experience in guiding and mentoring a team of ML engineers. Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems. Strong theoretical and practical background in NLP including experience with state-of-the-art LLM architectures optimized for handling large context and low inference cost. Advanced degree, ideally a Ph.D., in Computer Science, Electrical Engineering, or a related field with specialized research in areas such as machine learning, NLP, Large Language Models (LLMs), multi-modal foundation models, and generative AI techniques. Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI. Solid programming skills in Python and the ability to write clean, efficient, and well-documented code. 7+ years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects. Experience with distributed parallel training, large-scale multi-modal foundation and generative models strongly preferred Collaborate on modeling techniques to support the full spectrum of LLM tuning including prompt engineering, instruction tuning, Reinforcement Learning from Human Feedback (RLHF), parameter-efficient tuning, and fine-tuning strongly preferred. Familiarity with training multi-modal foundation models and relevant frameworks strongly preferred. Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments strongly preferred. Experience with RAG, dual encoders, or related fields strongly preferred. Experience with JAX strongly preferred. A track record of publications and contributions to the machine learning and natural language processing communities strongly preferred. Cognite is a global industrial SaaS company that was established with one clear vision: to rapidly empower industrial companies with contextualized, trustworthy, and accessible data to help drive the full-scale digital transformation of asset-heavy industries around the world. Our core Industrial DataOps platform, Cognite Data Fusion™, enables industrial data and domain users to collaborate quickly and safely to develop, operationalize, and scale industrial AI solutions and applications to deliver both profitability and sustainability. Visit us at and follow us on Twitter @CogniteData or LinkedIn: #J-18808-Ljbffr Cognite