Principal Machine Learning Engineer

Description

You will shape the company's AI strategy and act as a trusted advisor on ML work, designing architectures, leading large-scale deployments, and making sure solutions meet performance and security standards.

You need deep knowledge of advanced ML system architecture, scalable model deployment, and ML platform capabilities, plus working familiarity with modern AI application development. That covers LLMs, retrieval-augmented generation (RAG), prompt engineering, vector search, agent workflows, and model evaluation.

You will serve as the technical link between customer needs and product capabilities. This means working directly with stakeholders, gathering requirements, clarifying vague requests, and proposing solutions that deliver customer value.

The role calls for experience with large-scale ML architecture, advanced MLOps and observability, model governance and explainability, and tuning for both performance and cost. You will also mentor engineers and set standards others follow.

The skills listed for the role include design and architecture, leadership and impact, working with ambiguity, engineering excellence, quality focus, context engineering, AI output quality assurance, agentic AI practice, AI-assisted automation and prototyping, AI adoption, learning agility, collaboration, complex problem solving, creative thinking, and clear communication.

The company is an enterprise applications and business AI provider that has served finance, procurement, HR, supply chain, and customer experience customers for more than 50 years. The team builds and operates ML systems at scale.

Responsibilities

• Design and optimize large-scale ML systems, including LLM capabilities and the infrastructure behind them.
• Build new infrastructure and define architectural and operational standards for ML engineering.
• Ensure ML solutions meet business, performance, scalability, and governance requirements.
• Drive adoption of modern ML techniques and enable safe experimentation.
• Guide technical direction across products and make sure systems are production-ready and aligned with product goals.
• Mentor engineers and influence teams and products beyond your own group, including people who do not report to you.

Requirements

• 10+ years of software engineering experience and a record of delivering complex systems.
• Bachelor's degree in computer science, mathematics, physics, or a related field.
• Hands-on experience running AI/ML in production, including LLMs, RAG, prompt engineering, vector search, agent workflows, and model evaluation.
• Expertise in distributed systems design and architecture for large enterprise products.
• Strong programming skills, proficiency with ML frameworks, and a solid grasp of MLOps practices.
• Excellent English communication and the ability to work well in global, multicultural teams.

Conditions

The salary range is listed in the job posting. Final pay falls within that range and depends on education, skills, experience, location, and role scope, as decided during selection.

Any variable incentive is target-based, and actual payout depends on company and individual performance.

Applicant information is handled confidentially under EEO guidelines.

Use of AI in the application process must follow the company's published ethical guidelines, and breaches may lead to disqualification.

Benefits

• Variable incentive opportunities and additional benefits may be offered, subject to the terms of the relevant plans and policies.
• Benefits summary and eligibility are published on the company's North America benefits page.