Design and develop automation and semiconductor equipment modules, optimizing performance, yield, and manufacturability using Design of Experiments (DOE).
Lead the product development lifecycle from concept, design, and prototyping through validation and transition to high-volume manufacturing.
Collaborate with Engineering, Integration, Modules, and cross-functional teams to troubleshoot technical challenges and ensure alignment throughout project execution.
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Design, implement, and maintain automation systems for semiconductor equipment, focusing on enhancing operational efficiency and minimizing downtime
Collect, organize, and analyse production data to identify trends, optimize processes, and support decision-making in equipment automation and engineering.
Develop and maintain EA systems, including EAP, RMS, and ECS.
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Perform preventive and corrective maintenance to ensure the reliability, efficiency, and safe operation of plant equipment and systems.
Troubleshoot and resolve electrical, automation, and control system issues to minimize downtime and support continuous production.
Support the maintenance and optimization of electrical equipment, power distribution systems, instrumentation, PLC, HMI, SCADA, and industrial control systems.
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Partner with the current Senior Product Manager to lead AI and automation initiatives end-to-end, from discovery and problem definition through launch and iteration
Examine qualitative and quantitative signals (seller interviews, support tickets, behavioural analytics, etc. ) to identify where friction exists and shape AI / automation solutions to address
Design and run evals to validate model and feature performance, using pre / post comparisons, phased rollouts, and segment analysis
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Maintain the IT risk inventory to track identified issues and risks, including risk acceptances and remediation plans; provide governance, oversight, and reporting on issues and risks.
Lead the planning, scoping, execution, and documentation of risk management activities associated with technology and technology-related risks including cybersecurity and OT environments.
Identify, validate, and assess security risks; develop, socialize, and guide engineering and business teams through risk treatment plans.
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At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.
The Process Industries Division serves the mining, minerals processing, metals, cement, pulp and paper, battery manufacturing, and food and beverage, as well as their associated service industries. The Division brings deep industry domain expertise coupled with the ability to integrate both automation and electrical systems, increase productivity and reduce overall capital and operating costs for customers. For mining, metals and cement customers, solutions include specialized products and services, as well as total production systems. The Division designs, plans, engineers, supplies, installs and commissions integrated electrical and motion systems, including electric equipment, drives, motors, high power rectifiers and equipment for automation and supervisory control within a variety of areas including mineral handling, mining operations, aluminum smelting, hot and cold steel applications and cement production. The offering for the pulp and paper industries includes control systems, quality control systems, drive systems, on-line sensors, actuators and field instruments. Digitalization solutions, including collaborative operations and augmented reality, help improve plant and enterprise productivity, and reduce maintenance and energy costs.
Apply today or visit https://www.abb.com to learn more about the impact of our solutions across the globe.
Pathfind together with internal experts on automation of engineering data: explore with guidance from supervisor and technical experts enhancements of engineering data using shell scripts, python scripts and commercial tools such as schedulers (Jenkins), version control (Gitlab), requirements (JAMA) and anomaly tools (JIRA).
Learn to enhance coding and development: banking on your own coding skills and enhance with AI-assisted tools such as Gitlab co-pilot to speed up code and tool development
Develop new and enhance / maintain existing tools: user interfaces, databases used by microcontroller development teams using automation such as python
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Own the end-to-end activation of a flagship AI and Data learning program for strategic and top-tier APJ customer accounts.
Partner closely with account teams and Customer Enablement Architects to understand customer priorities and align training programs with business and technical objectives.
Coordinate training programs across executives, business users, technical users, and other relevant customer audiences.
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Maintain and support Automated Material Handling System (AMHS) equipment as part of the sustaining support team at the customer’s facility.
Monitor equipment performance, proactively identify issues, and carry out troubleshooting to minimize equipment downtime.
Perform error recovery, equipment repair, installation, modification, and upgrades in accordance with assigned Continuous Improvement Program (CIP) activities.
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Partner with the current Senior Product Manager to lead AI and automation initiatives end-to-end, from discovery and problem definition through launch and iteration
Examine qualitative and quantitative signals (seller interviews, support tickets, behavioural analytics, etc. ) to identify where friction exists and shape AI / automation solutions to address
Design and run evals to validate model and feature performance, using pre / post comparisons, phased rollouts, and segment analysis
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Internal tooling: Design and deploy AI-assisted workflows for reconnaissance, vulnerability prioritization, SOC alert triage/correlation, and draft report generation, with human validation built into every step.
New service line — AI Governance & Risk Assessment: Build and deliver assessments against ISO/IEC 42001, the NIST AI Risk Management Framework, and EU AI Act risk-classification requirements for clients deploying AI systems.
New service line — AI Red-Teaming: Design and run adversarial testing of client deployed LLM systems and AI agents — prompt injection, data leakage, jailbreak resistance, and agentic-workflow abuse cases.
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