COMPLETE Delivery Consultant Technology Expert Labs watsonx

Introduction
Joining the IBM Technology Expert Labs teams means you’ll have a career delivering world-class services for our clients. As the ultimate expert in IBM products, you’ll bring together all the necessary technology and services to help customers solve their most challenging problems. Working in IBM Technology Expert Labs means accelerating the time to value confidently and ensuring speed and insight while our clients focus on what they do best—running and growing their business.
Excellent onboarding and industry-leading learning culture will set you up for a positive impact, while advancing your career. Our culture is collaborative and experiential. As part of a team, you will be surrounded by bright minds and keen co-creators—always willing to help and be helped—as you apply passion to work that will positively impact the world around us.

Your Role and Responsibilities

As a Delivery Consultant, you will work closely with IBM clients and partners to design, deliver, and optimize IBM Technology solutions that align with your clients’ goals. In this role, you will apply your technical expertise to ensure world-class delivery while leveraging your consultative skills such as problem-solving issue- / hypothesis-based methodologies, communication, and service orientation skills. As a member of IBM Technology Expert Labs, a team that is client focused, courageous, pragmatic, and technical, you’ll collaborate with clients to optimize and trailblaze new solutions that address real business challenges.
If you are passionate about success with both your career and solving clients’ business challenges, this role is for you. To help achieve this win-win outcome, a ‘day-in-the-life’ of this opportunity may include, but not be limited to…
Understanding clients’ main challenges and developing solutions that helps them reach true business value by working thru the phases of design, development integration, implementation, migration and product support with a sense of urgency
Creating and executing agile plans where you are responsible for installing and provisioning assets, testing, migrating to production, and day-two operations
Conducting and participating in technical solution workshops
Developing successful relationships at all levels —from engineers to CxOs—with experience of navigating challenging debate to reach healthy resolutions.
Demonstrating a natural bias towards self-motivation, curiosity, initiative in addition to navigating data and people to find answers and present solutions
Strong collaboration and communication skills as you work across the client, partner, and IBM team

Required Technical and Professional Expertise

Proficiency in Python and object-oriented programming.
Experience consuming APIs and reading documentation.
Understanding of machine learning algorithms, statistical modeling, and data mining techniques.
Problem -solving skills and the ability to apply AI techniques to real-world scenarios, identifying the most suitable approaches for different use cases.
Knowledge of document understanding techniques, such as text extraction, classification, entity recognition, information retrieval, and semantic analysis.
Experience with data preprocessing, feature engineering, and data wrangling techniques to handle real-world datasets.
Hands -on experience in data science and machine learning frameworks and libraries such as TensorFlow, PyTorch, SciKit Learn, Pandas, Matplotlib, etc.
Understanding of key concepts in the Foundation Models literature and expertise in building and deploying them for real-world examples.
Hands on in prompt engineering and fine tuning pre-trained Foundation Models.
Proficiency with cloud technologies, particularly Kubernetes and Cloud Platforms like AWS, IBM Cloud or Microsoft Azure.
Understanding of MLOps concepts and technologies.

Preferred Technical and Professional Expertise

Proficiency in Python and object-oriented programming.
Experience consuming APIs and reading documentation.
Understanding of machine learning algorithms, statistical modeling, and data mining techniques.
Problem -solving skills and the ability to apply AI techniques to real-world scenarios, identifying the most suitable approaches for different use cases.
Knowledge of document understanding techniques, such as text extraction, classification, entity recognition, information retrieval, and semantic analysis.
Experience with data preprocessing, feature engineering, and data wrangling techniques to handle real-world datasets.
Hands -on experience in data science and machine learning frameworks and libraries such as TensorFlow, PyTorch, SciKit Learn, Pandas, Matplotlib, etc.
Understanding of key concepts in the Foundation Models literature and expertise in building and deploying them for real-world examples.
Hands on in prompt engineering and fine tuning pre-trained Foundation Models.
Proficiency with cloud technologies, particularly Kubernetes and Cloud Platforms like AWS, IBM Cloud or Microsoft Azure.
Understanding of MLOps concepts and technologies.