Machine Learning & AI Engineer - Managing Consultant
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
Job description
As a Managing Consultant ML/AI Engineer, you own a workstream end-to-end: taking an ambiguous ask, shaping it into a concrete design and plan, and delivering it with minimal guidance. You are responsible for the quality and correctness of everything in your workstream, and you begin to lift the engineers around you.
Your primary responsibilities will include:
- 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
Required technical and professional expertise
- 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.
Preferred technical and professional experience
About the company
A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
What Industries Outside of AI Are Hiring The Most AI Experts?
What Are Large Language Models?
Navigating the AI Shift
MLOps – What’s the deal behind it?