Senior Computer Vision AI and ML Engineer

At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we'll give you what you need to make it happen. It won't always be easy, growing takes grit. But at ABB, you'll never run alone. Run what runs the world.

This role sits within ABB's Robotics business, a leading global robotics company. We're entering an exciting new chapter as we've announced the plan for SoftBank Group to acquire ABB Robotics. SoftBank is a globally recognized technology group and investor/operator focused on AI, robotics, and next-generation computing. By joining us now, you'll be part of a pioneering team shaping the future of robotics—working alongside world-class experts in a fast-moving, innovation-driven environment.

This Position reports to:

Engineering Manager

Your roles & responsibilities

In this role you will drive the development of cutting-edge computer vision models for perception tasks such as segmentation, object detection, and 3D understanding. Architect real-time inference pipelines, lead technical validation efforts, and contribute to prototyping and evaluating emerging technologies for robotic manipulation and situational awareness. Act as a technical mentor for junior engineers and a bridge to the AI Technical Lead.

The work model for the role is #Li_hybrid

This role is contributing to the Robotics & Discrete Automation in Bangalore India.

• Design, train, and optimize deep learning models for core perception tasks—object detection, semantic and instance segmentation, and 3D scene understanding—using multi-modal sensor data (e.g., RGB-D).
• Devise labeling strategies, and tooling for automated annotation and QA. Contribute to dataset curation, balancing, and advanced augmentation techniques to simulate real-world illumination, occlusion, and high-mix variation scenarios.
• Develop continuous monitoring frameworks to assess model performance and reliability in real-world and simulated environments. Implement uncertainty estimation and failure detection methods to support fallback and recovery strategies in dynamic, unstructured conditions.
• Conduct proof-of-concept experiments to evaluate new algorithms, tools, and methodologies in computer vision, simulation, and perception. Translate research insights into practical prototypes that can inform roadmap and architecture decisions.

• MS or PhD in Computer Vision, Robotics, Machine Learning, or a related technical field or equivalent hands-on experience building and deploying perception systems in real-world robotics applications.
• 6 to 8+years of hands-on experience building deep learning models for perception tasks such as object detection, segmentation, and 3D understanding.
• Strong proficiency with Python, C++, and deep learning frameworks like PyTorch or TensorFlow; experience with ROS2 is a plus.
• Deep understanding of multi-modal sensor data (e.g., RGB-D, LiDAR) and experience working with synthetic data, real-world datasets, and augmentation strategies for robustness.
• Experience optimizing models for real-time inference, including latency reduction, throughput scaling, and deployment in closed-loop robotic systems. Skilled in evaluation methodologies, diagnostics, and performance monitoring across both simulation and real-world environments.
• Solid understanding of robustness and reliability techniques, including uncertainty estimation, perception failure detection, and recovery strategies for dynamic, unstructured environments.
• Strong problem-solving skills, ability to work independently, and experience collaborating in cross-functional robotics teams.

More about us

ABB Robotics & Discrete Automation Business area provides robotics, and machine and factory automation including products, software, solutions and services. Revenues are generated both from direct sales to end users as well as from indirect sales mainly through system integrators and machine builders.

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