ML/AI Engineer – Managing Consultant

IBM Consulting builds long-term client relationships and collaborates with companies across industries to shape their hybrid cloud and AI journeys. The Managing Consultant ML/AI Engineer owns workstreams end-to-end, translating ambiguous business needs into technical solutions, delivering maintainable ML/AI systems, mentoring junior engineers, engaging stakeholders, and communicating actionable results.

Responsibilities:

• Own a workstream: translate an ambiguous business need into a concrete technical approach, choose ML / AI methods and architecture, and defend technical implementation based on performance and trade-offs
• Design for maintainability: make design decisions that hold up over time; define the tests, validation, and checks that keep your workstream correct as it evolves and guarantee quality
• Design AI-accelerated workflows: decide where modern AI/LLM tooling fits (and where it doesn't) in your workstream, and set up those workflows for repeatable results
• Mentor: guide 1–2 junior engineers — review their work, unblock them, raise their bar
• Engage stakeholders: work directly with business/domain stakeholders to gather requirements and report progress
• Interpret Data and Communicate Results: Clearly and effectively communicate the results of Machine Learning initiatives to stakeholders, providing actionable insights and recommendations

Requirements:

• • Strong software engineering: designs maintainable, well-architected solutions; sets and enforces testing/validation for own scope; fluent with version control workflows and reviews
• • End-to-end ML/AI delivery: has independently taken ML/AI work from ambiguous problem to delivered solution, including method & algorithm selection and performance/validation
• • Judgment under ambiguity: frames problems, weighs trade-offs, and makes appropriate decisions
• • Detail & execution: plans and sequences a workstream; manages its risks and dependencies to on-time delivery
• • Modern AI tooling: effective, deliberate use of LLM/agentic tools to accelerate a team's work
• • Emerging leadership: experience mentoring or reviewing others' work
• • Communication & bridging business and technology: engages business/domain stakeholders directly; turns their requirements into a technical approach and explains trade-offs back in terms they understand
• Master's Degree