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IBM

ML/AI Engineer Senior Managing Consultant

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What they do

A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.

$168,439 / year median in the U.S.

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Job Description

  • Introduction
  • 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.
  • Your role and responsibilities
  • As a Senior Managing Consultant, you are the hands-on technical driver for a project.
You define the technical approach and drive the code and implementation, building the hardest, highest-risk parts of the solution. You guide a small team, keep the work correct, and pull the delivery through by example.

Your primary responsibilities will include:
  • Turn needs into Machine Learning /
AI Solutions:
Take high ambiguity from the business and define the problem worth solving. Design and implement systems and models to solve complex business problems, selecting relevant features and algorithms to achieve desired outcomes.
  • Set the engineering bar by example: establish standards for code quality, testing/validation, version control, and reproducibility — and hold them by writing to that bar yourself. You take on the pieces where getting the details right matters most.
  • Be the technical point of contact: translate business needs into the build and report progress to stakeholders on the solution.
  • Guide a small team: lead a team of 2-4. Assign and review work, unblock people, and grow them while building alongside them, not above them.
  • Own delivery of the solution: own the plan and sequencing, manage the technical risk, and keep the solution on track.
Communicate Results:
Clearly articulate the results of Machine Learning initiatives, providing actionable insights and recommendations to drive business outcomes.
    Drive Informed Decision-Making:
    Collaborate with stakeholders to integrate Machine Learning insights into business decision-making processes, driving informed strategic choices.
      Leverage Agentic AI & Modern LLMs:
      Claude, Copilot, LLM agents, prompt engineering, intelligent pipelines
        Design Scalable ML Platforms:
        MLOps infrastructure, enterprise integration
          Mentor & Collaborate:
          Cross-functional partnerships, team buildingThis job can be performed from anywhere in the US.
          • Required technical and professional expertise
          • Deep software-engineering discipline: sets testing/validation and reproducibility standards for a team and lives them in the code; known for rigor and correctness.
          • Technical leadership of a small team: has guided a small team's technical work, owning the approach and reviewing others, while remaining a primary builder.
          • Delivery ownership: credible at planning and sequencing a solution and managing its technical risk to delivery.
          Advanced ML/AI:
          broad command of ML/AI methods and modern AI/LLM/agentic approaches; sound judgment on where each applies.
          • Communication & bridging business and technology: the primary bridge between business and engineering for the solution.
          Comfortable being the technical point of contact, translating business needs into the build and technical reality back into decisions stakeholders can act on.

          IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

          Benefits

          • Dental Insurance