IBM is looking for an experienced AI/ML Engineer to join their Asset Engineering team within the IBM Consulting Client Innovation Centers. The role focuses on building and integrating innovative AI-powered solutions to address complex challenges. As part of this team, you will work on advanced technologies such as computer vision, machine learning, and GenAI to create high-performance solutions for clients.

Key Responsibilities

1. Develop and implement AI solutions. Build and integrate AI-powered features into IBM Inspection Suite for part and equipment inspection using AI models.
2. Enhance machine learning models. Work with models such as Yolo3 for object detection and classification. Aim to improve the quality, speed, and scalability of these models.
3. Collaborate with technical teams. Work closely with the CTO and the engineering team to architect, develop, and refine AI-driven solutions.
4. Build AI-powered systems. Design and deliver systems that can be used in real-world applications, ensuring seamless integration with mobile devices (e.g., CoreML, TensorFlow Lite).
5. Optimize AI model deployment. Assist in the conversion of models to optimized formats compatible with mobile environments.
6. Continuous improvement. Analyze and iterate on existing AI solutions to enhance performance, accuracy, and scalability.
7. Stay updated on AI trends. Continuously research emerging AI technologies and frameworks to ensure IBM remains at the forefront of AI innovation.

Required Skills and Experience

1. Machine Learning & GenAI. Strong understanding of machine learning and GenAI concepts, including knowledge of ethical implications like bias, fairness, and privacy.
2. Python and Data Science Libraries. Proficiency in Python with practical experience in libraries like NumPy, Pandas, and scikit-learn.
3. Computer Vision Expertise. Hands-on experience with Yolo, object detection, and classification models. Familiarity with segmentation and anomaly detection is a plus.
4. Containerization & Cloud. Solid experience in microservices development, Kubernetes (K8S), AWS, and Redhat OpenShift.
5. Large Language Models (LLMs). Familiarity with LLMs and experience in utilizing these models effectively, including prompt crafting and preparing data for analysis.
6. Graph & Vector Databases. Experience with Graph databases and Vector DB for AI and machine learning applications.
7. Relational Databases. Understanding of relational databases such as PostgreSQL and Redis.

Preferred Skills

1. Model Conversion. Experience in converting models to CoreML and TensorFlow Lite for mobile deployment.
2. AI Agent Workflow. Understanding of AI agent concepts and agentic workflows.
3. Caching Mechanisms. Experience with Redis or other service caching mechanisms to improve performance.

Why IBM? At IBM, you will be at the forefront of AI innovation, helping solve critical business challenges through technology. IBM fosters a dynamic and inclusive work culture that promotes continuous learning, growth, and collaboration. Working at IBM gives you the chance to contribute to AI-powered solutions that will impact industries globally, with the support of an innovative team and access to some of the most advanced technologies in the world.

Your Life at IBM. At IBM, we believe in the power of technology to change the world, and we are committed to creating an environment that is supportive, diverse, and inclusive. As an IBMer, you will have the opportunity to grow your career, experiment with new ideas, and work in a culture of continuous trust and collaboration.

Location Statement. IBM recommends that applicants apply to roles that match their experience and expertise. Candidates are advised to apply to no more than three roles per year for the best candidate experience.

Equal Opportunity Employer. IBM is an equal-opportunity employer, committed to building a diverse workforce. We provide equal employment opportunities regardless of race, gender, age, disability, or other protected status. We are committed to complying with all fair employment practices and creating a workplace where all employees can thrive.