As the senior individual contributor in machine learning, you will define the technical and strategic direction for AI within Operations and related domains. Your work will establish the foundation for reusable ML systems that power multiple products and influence the broader organization’s approach to intelligent automation.
Key Responsibilities
- Set the long-term vision for machine learning in operational contexts, aligning technical execution with business impact.
- Design scalable, reusable ML architectures and modeling standards adopted across teams.
- Lead the development of core systems that support diverse problem spaces and product initiatives.
- Establish best practices in model development, deployment, and MLOps, serving as a technical authority across the organization.
- Partner with engineering, product, and leadership to embed ML solutions into critical workflows.
- Champion ethical AI by ensuring models are fair, transparent, and resilient.
- Coach and develop machine learning practitioners at all levels, raising the collective expertise.
- Represent the organization in the global ML community through publications, talks, and open-source contributions.
Qualifications
You bring deep experience in building and scaling machine learning systems in complex, high-velocity environments. You have led the design of foundational ML frameworks and have a proven ability to translate advanced research into production-grade solutions. Fluency in Python, SQL, and frameworks like TensorFlow or PyTorch is essential. Experience with real-time inference, NLP, graph models, or reinforcement learning strengthens your profile. You communicate effectively across disciplines and thrive when navigating uncertainty to solve open-ended challenges.
Leadership through mentorship and technical influence is central to this role. You are passionate about growing talent and shaping organizational strategy through innovation and rigor.
