Machine Learning Architect

About the Company

This is a global enterprise software company focused on solving complex operational and planning challenges for large organizations. Its platform combines advanced analytics and machine learning to support decision-making across high-volume, real-world environments.

The business operates at scale, with a mature product suite and a strong emphasis on applied AI within a commercial setting. The team sits at the intersection of research and product, building capabilities that are deployed directly into customer-facing systems.

The Role

This is a senior individual contributor role for a Machine Learning Architect operating at a principal or staff level. You will work across multiple product areas, applying deep ML expertise to shape new capabilities, prototype ideas, and guide what moves into production. The role blends applied research with hands-on development and requires someone comfortable moving between theory, experimentation, and real-world constraints.

What You Will Do

• Develop and prototype machine learning approaches, particularly in NLP, and evaluate their fit for real product use cases
• Work across multiple teams and projects, contributing to different modeling challenges over time rather than a single fixed domain
• Translate research ideas into early-stage systems and guide their progression toward production-ready solutions
• Partner closely with engineering and product teams to ensure models are practical, scalable, and aligned with business needs
• Stay current with emerging ML techniques and assess where they can add measurable value to existing or future capabilities

What You Bring

• PhD in Computer Science, Machine Learning, AI, or a related quantitative field such as mathematics or physics
• Strong depth in machine learning fundamentals, including NLP (pre- and post-transformer approaches), with the ability to explain why models work, not just how to use them
• Hands-on experience building models and prototypes, with a balance of research and applied development work
• Working knowledge of classical ML techniques, with exposure to areas like forecasting considered a plus
• Solid programming ability (typically Python) and enough engineering experience to understand systems, pipelines, and how models integrate into products

Why This Role

This role offers a rare mix of applied research and real product impact. You will not be confined to a single team or problem space, instead contributing across a range of ML initiatives while helping shape what gets built and shipped. It suits someone who wants to stay hands-on, work on varied problems, and see their ideas move beyond experimentation into production systems.