VP/Technical Fellow Software Architecture – Generative AI Software Stack

The rapid advances of Artificial intelligence (AI), especially around Generative AI, and in particular LLMs like OpenAI GPT family of models, have driven innovations starting to disrupt existing market spaces across industry. Many businesses are betting on AI as the next growth opportunity.
Who you are:You must have deep technical experience working with methods and software technologies related to hosting, fine tuning, and training Large Language Models (LLMs), and other Generative AI models like 3D Point Cloud generation. A strong background developing cloud software for machine learning background is preferred, in addition to experience building LLMs applications and research. You will enable core models that will be the foundation of the product portfolio & tools that we are launching. You will regularly engage with product managers, and software engineering teams 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 other Generative AI models and contribute to transformative research with the vision of improving productivity, and safely including 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 software system design, architectural strategy on multiple Generative AI projects that involve a broad set of stakeholders.
• Drive end-to-end cloud part of Machine Learning projects that have a high degree of ambiguity, scale and complexity.
• Build software stack for training, and inference Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing 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 Generative AI and 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 çloud software and ML systems (Preferably 10+ years of industry experience in the relevant fields).
• 5+ years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
• Hands on experiencd
• 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 software  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.
• 5+ 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