Total 179 test engineer job vacancies in Education / Training category in Australia

The primary responsibility of this role is to deliver on an academic research project funded by MPA, where you will be part of the research team under the project titled: HarbourCraftSafe: Fire Resilinet Battery Room Design for Next-Gen Electric Habour. The project is in collaboration with two local industry collaborators.

Under this job title, you will develop a CFD modelling platform to evaluate the combustion, flammable and toxic gases emission and dispersion characteristics resulted from battery fires/thermal runaway in the battery room and beyond, considering the various common battery chemistries in eHC and atmospheric conditions. You will also need to experimentally characterise the heat release rate (HRR), flammable and toxic gases emissions of various types of batteries potentially deployed in eHC through reduced scale testing. Lastly, you will also need to evaluate the various gas monitoring sensors performance in detecting the battery gas releases for remote monitoring and early detection, and evaluate the potential fire suppression strategies on battery fires.

Job Responsibilities: 

• Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.

• Undertake these responsibilities in the project:
• Assists in co-supervision of final year projects (FYP) or capstone projects students under the Project PI.
• Meeting the deliverables by carrying out the computational simulations and experimental studies planned for under the scope of work of the projects within the timeframe to meet the deliverables.
• Assists the PI in drafting of reports, conference proceedings and journal articles based on the outcome of the projects.
• Prepares and shares fortnightly report of results from the computations with the PI.
• Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
• Coordinate procurement and liaison with vendors/suppliers.
• Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

Job Requirements:

• Master or Ph.D (preferred) in Mechanical Engineering, Marine and Offshore Engineering or related fields.
• Strong knowledge and experience in battery fire simulation is high advantageous.
• Hands on experience on experimental studies
• Familiarity with CFD applications working on industrial related projects using high performance computing clusters would also be advantageous
• Strong foundation in Fluid Dynamics
• Strong prior experience in CFD – particularly in battery fire combustion and spread.
• Strong skills in turbulence modelling, CFD mesh generation in complex 3D geometries.
• Proficient in handling large data sets and the ability to analysis and interpret results.
• Experience in commercial CFD package such as ANSYS package and FDS is preferred. Candidate preferably should be familiar and have sufficient experience in using ANSYS FLUENT and FDS, Meshing tool and post-processing software.
• Able to work independently with strong data analytical skills, communication and interpersonal skills.

Key Competencies:

• Proficient in Ansys Fluent or FDS Simulation
• Strong foundation in Fluid Dynamics
• Able to work independently with strong data analytical skills, communication and interpersonal skills.
• Able to build and maintain strong working relationships with people within and external to the university.
• Self-directed learner who believes in continuous learning and development
• Proficient in technical writing and presentation
• Possess strong analytical and critical thinking skills
• Show strong initiative and take ownership of work

The Alibaba-NTU Global e-Sustainability CorpLab (ANGEL) represents a key collaboration between Alibaba Group and Nanyang Technological University (NTU). Supported by the Singapore RIE2025 Fund, ANGEL creates and deploys impactful green digital technologies for global sustainability.

ANGEL’s mission aligns seamlessly with Singapore’s national objectives, such as the Singapore Green Plan 2030 and the Singapore Smart Nation Initiative. ANGEL’s work in developing sustainable and equitable digital solutions and promoting a sustainable and green lifestyle will contribute to a smaller carbon footprint. Its holistic approach will help to secure a brighter, more sustainable future for humanity. 

ANGEL is looking for a motivated Research Engineer to support intensive research efforts and the delivery of projects.

Key Responsibilities:

• Review the literature related to UAV communications and networking

• Develop new AI algorithms for UAV networking and management

• Implement and test the algorithms under realistic scenarios

• Evaluate performance of the proposed algorithms and compare the algorithms with benchmarks

• Publish the results in top-tier journals and conferences

Job Requirements:

• Bachelor’s degree in electrical or computer engineering or computer science

• Good publication record with papers accepted/published in top-tier journals and conferences

• Good research experience in AI and machine learning as well as wireless networking

• Independent, highly analytical, proactive and a team player

• Excellent teamwork and verbal, written communication skills

We regret to inform that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28Catalyst-Development%29/32289-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The staff would support at least one project under the supervision of the Principal Investigator (PI). The scope of the project is on catalyst development for fuel conversion. The staff will need to develop a well-justified approach to achieve a goal once a problem statement and/or a research scope are defined by the PI and the staff. The staff will need to execute the plan experimentally and interpret the data critically. The staff will need to report to the PI proactively and take the initiative to propose changes to the plan when the project faces a technical challenge. The staff will need to draft manuscripts and attend conferences to publicise the project findings. The staff will need to support other team members.

Qualifications

A well-qualified candidate should:

• Possess a Bachelor’s degree in Chemical Engineering, Chemistry, or a similar/equivalent discipline;
• Be passionate about research;
• Be an expert of catalyst development;
• Possess strong spoken and written communication skills at professional level;
• Be a good team player;
• Excellent publication record in related areas.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28Catalyst-Development%29/32288-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The staff would support at least one project under the supervision of the Principal Investigator (PI). The scope of the project is on catalyst development for fuel conversion. The staff will need to develop a well-justified approach to achieve a goal once a problem statement and/or a research scope are defined by the PI and the staff. The staff will need to execute the plan experimentally and interpret the data critically. The staff will need to report to the PI proactively and take the initiative to propose changes to the plan when the project faces a technical challenge. The staff will need to draft manuscripts and attend conferences to publicise the project findings. The staff will need to support other team members.

Qualifications

A well-qualified candidate should:

• Possess a Bachelor’s degree in Chemical Engineering, Chemistry, or a similar/equivalent discipline;
• Be passionate about research;
• Be an expert of catalyst development;
• Possess strong spoken and written communication skills at professional level;
• Be a good team player;
• Excellent publication record in related areas.

We are seeking a Research Engineer to design, implement, and integrate Visual-Language Models (VLMs) into autonomous mobile robots platform. The role focuses on enabling high-level semantic reasoning, perception–language grounding, and decision-making in robotic systems. The engineer will interface VLMs with navigation, mapping, and control pipelines to support end-to-end system experimentation. Responsibilities include building simulation environments, conducting experimental evaluations, and supporting rapid prototyping. The role contributes to translating simulation-validated methods toward real-world robotic deployment and bridges robotics simulation, multimodal AI, and autonomous navigation research.

Key Responsibilities:

• Design, implement, and integrate Visual-Language Models (VLMs) into simulation and robotic platforms to enable semantic reasoning, perception–language grounding, and decision-making.

• Interface VLM-based modules with robot navigation, mapping, localization, planning, and control systems to support end-to-end autonomous operation.

• Build and maintain simulation environments, multimodal datasets, and evaluation frameworks, handling data volumes from tens to hundreds of gigabytes.

• Conduct experimental studies using GPU-enabled computing resources for model training, inference, and simulation-based evaluation.

• Support rapid prototyping and iteration of research ideas, from concept to validated robotic systems and demonstrations.

• Collaborate with and provide technical support to research staff and students across multiple projects.

• Contribute to research outputs, including publications, technical disclosures, patents, and autonomous robot demonstrations.

• Apply and recommend engineering best practices that promote reproducibility, maintainability, and research productivity.

Job Requirements:

• Bachelor’s degree (BEng/BSc) in Robotics, Computer Science, Electrical or Mechanical Engineering, or a related discipline; candidates with strong robotics and autonomous system experience from other disciplines may be considered.

• Proficiency in Python, with experience in ROS/ ROS2 and Linux-based development environments.

• Familiarity with robotic simulation platforms and 3D modelling tools.

• Hands-on experience in autonomous robotics projects; exposure to deep learning or reinforcement learning is a plus.

• Strong problem-solving ability, collaborative and independent work style, willingness to learn new tools.

We regret that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-%28AI-Empowered-Reasoning-of-Granular-System%29/32291-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are hiring a Research Engineer (RE) to develop a novel knowledge-driven AI method for understanding the interaction between solid and fluid interaction. The selected RE is required to:

•    Developing a novel knowledge-driven AI framework for implementing CFDDEM simulation.
•    Validating the proposed framework and applying it to granular materials related engineering such as geotechnical, and chemical engineering.

Job Requirements

•    Possess at least a bachelor’s degree. 
•    Demonstrate relevant research or professional background, aligned with the development of the topic. 
•    Relevant experience in multiple areas is highly desirable.
•    Exhibit proficiency in coupled CFD DEM modelling (C++) and AI-related algorithms (python).
•    Display strong teamwork capabilities.
•    Excellent written and spoken communication skills.
•    Open to fixed-term contract.
•    Please note that only shortlisted candidates will be contacted.

Responsibilities

• Conduct experimental research on various properties of the Company’s products, as well as analysis and tests to investigate the chemical phenomena of products.
• Responsible for new product testing, development and prototype production; as well as assisting customers during material evaluation and qualification phases with the Company’s products.
• To work closely with customers in the development of suitable material configurations to meet customer needs and providing technical support to them.

Requirements:

• Degree in Chemical Engineering / Chemistry / Materials Science / Polymer.
• At least 1 – 2 years of working experience in similar capacity. Those with more than 3 years of experience will be considered for Senior Engineer's position.
• Knowledge of polymer science and semiconductor materials composition.
• Knowledge of IC package encapsulant and semiconductor back-end processes.
• Knowledge in material characterization and/or FA equipments is preferred.
• Experience in DOE, FEM and numerical analysis would be advantageous.
• Innovative, meticulous, analytical with initiative.
• Must be a team player and strong work commitment.

As a University of Applied Learning, the Singapore Institute of Technology (SIT) collaborates actively with industry in our research work. We seek a motivated candidate who is keen on rigorous research, the practical applications of code exfiltration and reverse engineering as well as security penetration testing. 

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of a research team to investigate and determine potentially critical Commercial Off-The-Shelf (COTS) drone system vulnerabilities impacting confidentiality, integrity and availability.

Key Responsibilities

• Participate in the research project with Principal Investigator (PI), Co-PIs and research team members to ensure all project deliverables are met.
• Undertake or help guide work and demonstrations in the following tasks:

1. Code exfiltration and binary reverse engineering.
2. Study, understand and analyse mobile platform applications.
3. Android app reverse engineering (Drone apps)
4. Static and Dynamic analysis(experience in tools like Frida, Burp, Wireshark)
5. Develop AI-assisted agents for automated firmware analysis and exploration
6. Build a controlled firmware-replica environment for evaluating protocol security
7. Design, develop and test control augmentation techniques.
8. Adaptation of developed techniques for more generic use.

• Perform project documentation and crafting of research papers.
• Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
• Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

 Job Requirements

• A good degree in Computer Science / Engineering or higher.
• Proficiency with code exfiltration and reverse engineering.
• Proficiency with penetration testing techniques and tools.
• Proficiency with software scripting and development work on desktop and / or mobile platforms.

Key Competencies

• Self-directed learner who believes in continuous learning and development.
• Possess strong analytical and critical thinking skills.
• Show strong initiative and take ownership of work.
• Proficient in technical writing and presentation.
• Able to build and maintain good working relationships with people within and external to the university.

CYSREN was established to address these concerns through multi-disciplinary research and development around cybersecurity, leveraging NTU’s core competencies in Engineering, Exact Sciences, International Studies and Business, among others.

We have a dedicated core team that uses its domain expertise and global experience while leveraging on NTU’s vibrant research culture and comprehensive R&D infrastructure to deliver state-of-the-art R&D projects. We engage with local as well as global agencies and industry partners to develop capabilities for a number of areas of strategic importance including:

• cyber worthiness of autonomous vehicles

• cyber risk management, advanced threat intelligence

• secure-by-design for IoT and policy

• governance of cybersecurity

For more details, please view https://www.ntu.edu.sg/cysren.

Responsibilities:

• Lead the architecture, design, and development of software systems for the Agentic AI framework

• Drive the development of autonomous AI agent systems, including reasoning, planning, memory, and tool integration capabilities

• Take ownership of end-to-end system delivery, from concept and prototyping to evaluation and deployment

• Design and implement scalable, secure, and high-performance AI platforms, leveraging modern cloud-native and distributed architectures

• Establish and enforce engineering best practices, including coding standards, testing frameworks, and documentation

• Lead technical experimentation and evaluation, including benchmarking, performance optimisation, and system validation

• Mentor and guide junior engineers and researchers, providing technical direction and oversight

• Collaborate with internal stakeholders, external partners, and industry collaborators to translate research into real-world applications

• Contribute to research outputs, including technical reports, publications, and intellectual property development

• Support project planning, milestone tracking, and delivery of funded research objectives

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related discipline.

• Minimum 8 years of relevant experience in software engineering, AI systems development, or   research engineering roles

• Strong programming experience in Python or similar languages

• Knowledge of machine learning, AI systems, or autonomous agents

• Experience with scalable software systems and cloud-based development environments

• Familiarity with software engineering practices including version control and testing

• Strong analytical, problem-solving, and communication skills

• Ability to lead across multidisciplinary teams

We regret to inform that only shortlisted candidates will be notified.

We are looking for motivated candidates to join the Advanced Manufacturing & Semiconductor Division (AMS) at the Institute of High Performance Computing (IHPC), A*STAR as a Research Engineer. The candidate will support research and development in AI for Science and scientific machine learning, with a focus on implementing and scaling Physics Foundation Models (PFM) for modelling complex physical systems in advanced manufacturing and semiconductor applications.

This work involves integrating neural operators, graph-based numerical solvers, and deep learning architectures to develop next-generation computational modelling tools. You will work closely with researchers and engineers to build robust computational frameworks and accelerate physics-based simulations using machine learning.

The key scope of work includes:

• Implementing and optimizing neural operator architectures for modelling PDE-governed physical systems.
• Developing graph-based representations of numerical solvers and integrating them into machine learning frameworks.
• Building and maintaining machine learning pipelines for scientific simulations, including data generation, training, and evaluation.
• Integrating deep learning models with physics-based simulation workflows.
• Optimizing computational performance using GPU acceleration and high-performance computing platforms.
• Supporting the development of research prototypes and experimental platforms.
• Collaborating with interdisciplinary teams working on machine learning, physics, and engineering applications.

Job Requirements:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computational Physics, Applied Mathematics, or related disciplines.
• Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch or JAX.
• Experience with scientific computing, numerical simulation, or PDE-based modelling is desirable.
• Familiarity with graph neural networks, neural operators, or physics-informed machine learning is an advantage.
• Experience with GPU computing, parallel computing, or high-performance computing environments is a plus.
• Good software engineering practices, including version control and reproducible research workflows.
• Strong problem-solving skills and ability to work effectively in a collaborative research environment.

We welcome engineers who are eager to build impactful technologies at the intersection of machine learning, physics, and advanced manufacturing.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

We are looking for motivated candidates to join the Advanced Manufacturing & Semiconductor Division (AMS) at the Institute of High Performance Computing (IHPC), A*STAR as a Research Engineer. The candidate will support research and development in AI for Science and scientific machine learning, with a focus on implementing and scaling Physics Foundation Models (PFM) for modelling complex physical systems in advanced manufacturing and semiconductor applications.

This work involves integrating neural operators, graph-based numerical solvers, and deep learning architectures to develop next-generation computational modelling tools. You will work closely with researchers and engineers to build robust computational frameworks and accelerate physics-based simulations using machine learning.

The key scope of work includes:

• Implementing and optimizing neural operator architectures for modelling PDE-governed physical systems.
• Developing graph-based representations of numerical solvers and integrating them into machine learning frameworks.
• Building and maintaining machine learning pipelines for scientific simulations, including data generation, training, and evaluation.
• Integrating deep learning models with physics-based simulation workflows.
• Optimizing computational performance using GPU acceleration and high-performance computing platforms.
• Supporting the development of research prototypes and experimental platforms.
• Collaborating with interdisciplinary teams working on machine learning, physics, and engineering applications.

Job Requirements:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computational Physics, Applied Mathematics, or related disciplines with at least 5 years of relevant experience.
• Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch or JAX.
• Experience with scientific computing, numerical simulation, or PDE-based modelling is desirable.
• Familiarity with graph neural networks, neural operators, or physics-informed machine learning is an advantage.
• Experience with GPU computing, parallel computing, or high-performance computing environments is a plus.
• Good software engineering practices, including version control and reproducible research workflows.
• Strong problem-solving skills and ability to work effectively in a collaborative research environment.

We welcome engineers who are eager to build impactful technologies at the intersection of machine learning, physics, and advanced manufacturing.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

This project focuses on federated causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy causal analysis across distributed datasets while preserving privacy. The successful candidate will be responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference algorithms through simulations and live demonstrations.

Key Responsibilities

• Participate in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met.
• Derivation of novel performance metrics for federated causal inference algorithms.
• Analysis of causal inference models in federated settings using synthetic and real-world datasets.
• Design and development of novel federated causal inference algorithms and associated software APIs.
• Validation of algorithms via simulations and live demonstrations.

Job Requirements

• A Master's degree or higher in Computer Engineering, Computer Science, Data Science, Statistics, or equivalent.
• Strong theoretical background in statistics and machine learning.
• Knowledge of the basics of federated learning and causal inference is highly encouraged.
• Proven track record in research and development of machine learning algorithms.
• Proficiency in algorithm development using Python and ML frameworks such as PyTorch or TensorFlow.

Key Competencies

• Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.
• Able to build and maintain strong working relationships with people within and external to the university.
• Self-directed learner who believes in continuous learning and development.
• Proficient in technical writing and presentation.
• Possess strong analytical and critical thinking skills.

The Centre for Advanced Technologies in Online Safety (CATOS; https://www.catos.sg) was established in 2023 to host Singapore's Online Trust and Safety (OTS) Programme, a national research programme that leads the advancement of whole-of-nation technology capabilities to monitor and tackle online harms. The Systems Engineering Pillar of CATOS focuses on translational research and development, including evaluating, testing and integrating research output into needle-moving applications. One of the major outcomes will be a technological platform with an integrated suite of deep tech OTS engines, which analyses various internet sites and platforms for fast-trending harmful online content, such as non-factual claims, deepfakes, and hateful and toxic content. Different combinations of OTS engines can then be integrated and adapted to address the specific requirements of various stakeholders.

This role will be responsible for systematically evaluating AI models and datasets to understand the strengths and weaknesses of existing tools in this field and identify ways to adapt promising tools to their intended applications. The work will create valuable knowledge to inform end-users and technology researchers, helping to ensure that the technologies from CATOS and its partners are of desirable performance and robustness for the intended use cases and applications.

The candidate will assume the following roles and responsibilities:

• As a Research Engineer, contribute to the evaluation of emerging technologies and data underneath the technologies.
• Collaborate with senior team members, stakeholders and cross-functional teams to incorporate requirements that arise from the evolving landscape.
• Contribute to key CATOS events that are aimed at engaging the research, industry, government agencies, NGOs and the general public

JOB REQUIREMENT:

• A Bachelor / Master degree in Computer Science / Information Technology / Computer Engineering / Information Systems / Data Engineering / Computational Social Science or equivalent.
• Demonstratable experience in using machine learning / deep learning frameworks and models.
• Proficient with programming languages (e.g., Python, Java, C/C++, MATLAB) and tools. (e.g., Jupyter Notebook, VS Code)
• Ability to quickly develop and iterate on prototypes.
• Experience in using (Multi-Modal) Large Language Models is valued.
• Good communication and interpersonal skills for working in a multicultural work environment.
• Candidates with no experience may apply.

Our research and engineering work is highly interdisciplinary, agile, and pragmatic in nature.

• We expect everyone to take ownership of their role, responsibilities, and tasks.
• We encourage everyone to speak up when they have feedback or ideas for improvement.
• We provide honest feedback to one another, which can be tough at times, but it fosters rapid learning.
• We care about each other's professional growth and well-being.

When applying, please share at least two representative research projects or publications that you have developed independently or contributed to significantly.

Please note that only shortlisted candidates will be notified.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

At the Institute of High Performance Computing (IHPC), A*STAR, we drive innovation at the intersection of artificial intelligence and healthcare. Our mission is to build large language models (LLMs) and multimodal foundation models that can transform clinical decision support, biomedical discovery, and public health.

We are looking for AI Engineer with strong applied AI skills ready to build large-scale systems. You will contribute to innovations that make real impact in healthcare.

Key Responsibilities:

Research & Development

• Develop novel architectures, training strategies, and optimization methods for LLMs and multimodal foundation models.
• Advance instruction tuning, reinforcement learning (RLHF/GRPO), retrieval-augmented generation (RAG), and knowledge-grounded reasoning in medical AI.
• Design and implement multimodal learning pipelines that integrate text, imaging, omics, and real-world clinical data.

Translation & Collaboration

• Prototype AI systems for clinical and biomedical applications (e.g., decision support, conversational AI, population health, drug discovery).
• Benchmark models against state-of-the-art healthcare AI datasets and evaluation frameworks.
• Collaborate with industry and healthcare partners to enable translation, licensing, and commercialization.

Scientific Leadership

• Publish in top-tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL) and high-impact biomedical journals (e.g., Nature Medicine).
• Contribute to open science initiatives (datasets, model releases, benchmarks).
• Secure funding through collaborative research proposals with academia, healthcare institutions, and industry.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related fields.
• Proven hands-on experience in implementing and optimizing machine learning models.
• Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, JAX).
• Experience with large-scale training, HPC workflows, or ML engineering pipelines.
• Experience in large-scale LLM and foundation model training and deployment.
• Experience with medical or biomedical data (EHR, clinical notes, imaging, genomics).
• Familiarity with biomedical ontologies and knowledge graphs (UMLS, SNOMED CT, PubMed).
• Understanding of AI ethics, safety, and regulatory considerations in healthcare.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

Job Description

Be part of an exciting FAB Operations Team working on cutting-edge process technologies.

Job Responsibilities:

• Looking for reliable individual - Operate multiple type of semiconductor equipment in cleanroom environment.
• Ability to use computer-based programs and applications to perform daily work/duties.
• Operate equipment based on the required process specifications (e.g. procedures, change notifications, etc.).
• Participate actively and be responsible in assigned on-the-job assignments and other required trainings when requested. Provide machine operations coverage and backup supports when necessary.
• Adequate understanding of the Equipment in-charge, monitor performance, timely communication with Engineers-in-charge to perform equipment errors recovery promptly when necessary.
• Demonstrate excellent teamwork to promptly execute process sequences and data collections if required.
• Always follow safety protocols & rules in the Clean Room.
• Ensure 6S in the work environment and promptly report hazards/ suspicious/ abnormal activities or personnel if any identified.
• Address potential areas for improvements such as wafers processing cycle time, Equipment utilization, Safety/ Compliances, and cost savings.

Job Requirements:

• Diploma/Degree in MicroElectronics/Electrical/Mechanical/Chemical Engineering or equivalent.
• Understanding on semiconductor process - at least 1-3 years of experience in semiconductor processes (Photolithography, Dry/Wet Etch/Cleans, ThinFilms, Diffusions, Chemical mechanical Polishings, Metrology etc.)
• Must be a self-starter, dependable and highly motivated.
  
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