• 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 Data Engineer with expertise in Machine Learning, you build reliable, well-engineered software that applies machine learning and modern AI techniques to real business problems. You take well-defined tasks and features and deliver them correctly, on time, and to a standard others can build on. using modern AI tooling to work faster without cutting corners on quality.
• Build ML/AI components: implement models, features, and application logic against clear specifications, choosing appropriate methods from established approaches.
• Engineer for quality: write clean, readable, tested code; use version control, code review, and the team's standards as a matter of habit. Get the details right and verify your own work against acceptance criteria before it's called done.
• Evaluate & validate: measure model/solution performance with the right metrics and confirm outputs are correct, and not just that the code runs.
• Accelerate with modern

AI:

use LLM/agentic tools (e.g., Claude, Copilot) to move faster, while reviewing and validating everything the AI produces.

Communicate:

clearly present your results and progress to the team; flag blockers and slippage early.

Bridge Business and Technology:

Translate requirements, evaluate against business metricsThis job can be performed from anywhere in the US.

• Required technical and professional expertise
• Applied ML/AI foundations: working knowledge of core ML concepts and common frameworks (e.g., scikit-learn, PyTorch/TensorFlow); able to apply them to defined problems.
• Data fluency: able to work with data, interpret results, and identify relevant features.
• Detail & execution: a track record of delivering assigned work reliably and accurately.

Data Analysis Skills:

Ability to interpret statistical data and identify relevant features to inform solution development.

• Modern AI tooling: exposure to LLM/agentic developer tools and prompt basics. Use Claude, Copilot, LLM agents for acceleration
• Solid software engineering: proficiency in Python (or similar); comfortable with version control, testing, and code review. You care about correctness and readable, maintainable code.
• Communication & business awareness: explains technical work clearly to teammates and non-experts, and is starting to connect the "why" (business need) to the "how" (technical solution).

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.