เงื่อนไขการค้นหา

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Statistical Analysis, Software Development, Kubernetes, Python, NoSQL, ETL, English

ประเภทงาน:

งานประจำ

• Key Accountabilities.
• Design and work on all aspects of bringing ML models into production, develop CI/CD pipelines by collaborating with other disciplines such as data engineering, application development, cloud infrastructure, and security to implement AI solutions in production.
• Work collaboratively with data scientists along the machine learning lifecycle from data pipeline, data preparation, model deployment, and model monitoring.
• Understand and assess AI/ML industry trends to leverage technologies, continuously improve efficiency and effectiveness of the existing algorithms; as well as to understand their impact on our AI/ML solutions.
• Provide architectural and technical leadership to drive AI/ML capabilities.
• Initiate innovation and development projects to continuously improve the overall efficiency of the team in the engineering aspect.
• Professional Knowledge & Experiences.
• Degree in computer science or related fields, with concentration in Machine Learning/AI engineering.
• At least 3 years of experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, Neural Networks, etc.). Expertise with Data Science and experience with manipulating/transforming data, model selection, model training, and deployment at scale.
• Knowledge and experience in database technologies, such as SQL, NoSQL, and demonstrate knowledge of databases (Google BigQuery preferred), Data ETL framework (Airflow), ML libraries (scikit-learn, XG Boost, PyTorch, etc.), ML Frameworks (Kubeflow, MLFlow, etc.).
• Knowledge and experience in Kubernetes technology. Be able to develop CI/CD pipeline, deploy workloads, configure and monitor jobs on kubernetes clusters.
• Significant proficiency in Python. Experience working with GCP is preferrable.
• Ability to work in cross functional teams, have team-work mindset, self-motivation.
• Excellent written and verbal communication skills in English.
• Additional Desirable Qualification.
• Solid grounding in statistics, probability theory, data modelling, machine learning algorithms and software development techniques and languages used to implement analytics solutions.
• Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.).
• CORE Competencies.

ประสบการณ์:

4 ปีขึ้นไป

ทักษะ:

Production planning, Procurement, Accounting, Automation, English

ประเภทงาน:

งานประจำ

• Production planning & job dispatch.
• Plan daily production capacity and scheduling across digital, large format (HP Latex), and DTF streams, including multi-press readiness.
• Decide job routing in-house vs. outsource based on cost and lead time per job.
• Dispatch all jobs to the Gogoprint factory and external printing partners daily before the 4:00 PM cutoff, across offset, digital, large format, DTF, and promotional product categories.
• Issue prioritized daily job sheets to the production team (offset before 8:00 AM, digital before 8:30 AM) covering cutting, folding, lamination, kiss-cutting, die-cutting, and bookbinding.
• Coordinate directly with printing partners to resolve issues arising during production.
• Procurement & replenishment.
• Purchase all production materials and consumables: paper and sticker sheets for the digital presses, Ricoh toner, HP Latex inks and printheads, DTF inks and fabric rolls, large-format substrates and lamination rolls, corrugated boxes, and miscellaneous supplies.
• Place internal factory orders for customer packaging (business card boxes, shipping cartons).
• Keep replenishment cycles ahead of production needs so that no press or post-press station stops for lack of materials.
• Inventory control.
• Run the monthly stock reconciliation and report results to the Accounting team.
• Oversee stock-level monitoring routines performed by machine operators and maintain accurate inbound records for paper, substrates, and consumables.
• Supplier coordination & continuous improvement.
• Act as the day-to-day interface with our printing partner network and contribute to quarterly supplier performance reviews (OTIF, quality, price).
• Serve as backup for factory HSE routines, production complaint handling, and new product industrialization projects.
• Cover planning and procurement duties of teammates during leave periods, and propose improvements to job sequencing, automation, and replenishment processes.
• What Success Looks Like.
• Daily dispatch cutoffs consistently met across all product streams.
• Zero production stoppages caused by material stockouts.
• Accurate monthly inventory reconciliation with no unexplained variances.
• Routing decisions that protect gross margin without compromising delivery promises.
• Must Have.
• 4+ years of experience in supply chain, production planning, or procurement, ideally in printing or a fast-paced manufacturing environment.
• Thai native speaker with working English (supplier communication, systems, and internal documentation are in English).
• Strong command of Excel / Google Sheets; comfortable working in ERP, back-office, and e-commerce order management tools.
• Structured and deadline-driven; able to operate reliably against hard daily cutoffs.
• Hands-on and at ease on a factory floor, working closely with operators and suppliers alike.
• Nice to Have.
• Knowledge of offset, digital, or large-format printing processes.
• Experience negotiating with material suppliers or print subcontractors.
• Annual bonus and salary increment.
• Social Security.
• Health Insurance OPD/IPD.
• 8 days annual leave.
• Public Holidays.
• Career growth opportunities.

ประสบการณ์:

15 ปีขึ้นไป

ทักษะ:

Electrical Engineering, Industrial Engineering, Enthusiastic, Architecture, Electronics

ประเภทงาน:

งานประจำ

• Lead, grow, and develop a distributed team of AI/ML engineers who work across manufacturing sites and solve site-specific operational problems.
• Establish the technical vision, engineering standards, delivery practices, and talent strategy for manufacturing AI across the organization.
• Create a strong partnership model with plant leadership, manufacturing engineering, process engineering, yield, quality, operations, IT, and enterprise data teams.
• Balance local site responsiveness with reusable platforms, common architectures, shared components, and responsible AI practices that scale across plants.
• Set and execute a multi-year roadmap for AI/ML applications in manufacturing, aligned to business priorities and measurable operational outcomes.
• Identify and prioritize high-impact opportunities across process optimization, yield improvement, visual inspection, defect classification, predictive maintenance, anomaly detection, root-cause analysis, quality, scheduling, and engineering productivity.
• Guide the architecture, design, development, validation, deployment, and lifecycle management of production-grade AI/ML systems used in manufacturing workflows.
• Define engineering patterns for data pipelines, feature and model management, experiment tracking, APIs, user interfaces, monitoring, cybersecurity, reliability, and model performance management.
• Ensure solutions work with real manufacturing data and systems, including MES, SPC, QMS, equipment and sensor data, inspection systems, yield systems, ERP, databases, engineering reports, and other structured and unstructured sources.
• Drive disciplined problem definition and value measurement, connecting technical delivery to improvements in cycle time, throughput, yield, scrap, quality, cost, safety, and decision speed.
• Partner with site teams to understand workflows, constraints, process variation, data quality, user needs, and adoption barriers; ensure solutions are usable by engineers, operators, and business stakeholders.
• Build and maintain strong relationships with senior manufacturing and technology leaders, communicating technical tradeoffs, risks, investment needs, and results with clarity.
• Promote effective use of classical machine learning, deep learning, computer vision, optimization, statistical methods, LLMs, and generative AI where they are fit for purpose.
• Establish governance for responsible, secure, explainable, and maintainable AI in manufacturing, including validation, human oversight, change control, and production support.
• 15+ years of progressive experience in software engineering, AI/ML engineering, data science, or a closely related technical discipline, including significant leadership experience.
• Bachelor's or master's degree in engineering, computer science, electrical engineering, industrial engineering, data science, or a related field; advanced technical education is preferred.
• Deep hands-on understanding of software engineering practices, distributed systems, cloud or edge architectures, APIs, data platforms, testing, observability, security, and production operations.
• Practical knowledge of manufacturing processes, process variation, yield, quality systems, equipment data, inspection, traceability, root-cause analysis, and the realities of plant operations.
• Willingness and ability to travel 30% or more to manufacturing sites and partner locations.
• Preferred Qualifications.
• Experience in semiconductor, photonics, electronics, optical components, precision manufacturing, or other high-volume advanced manufacturing environments.
• Experience with manufacturing software and data ecosystems such as MES, SPC, QMS, ERP, equipment automation, inspection platforms, historian systems, and yield management systems.
• Experience scaling AI/ML capabilities across multiple plants, regions, or business units with different processes, data maturity, and operating models.
• Experience applying generative AI, knowledge retrieval, agentic workflows, or LLM-enabled tools to manufacturing, engineering, quality, or operations use cases.
• We are an equal opportunity employer and value diversity at our company.
• We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
• We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
• Please contact us to request accommodation.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Data Analysis, Enthusiastic, Architecture, Electronics, Automation

ประเภทงาน:

งานประจำ

• Serve as a forward deployed AI engineer embedded with the Bangkok manufacturing team to identify high-impact AI opportunities across process engineering, yield improvement, visual inspection, quality control, operations, and reporting workflows.
• Partner with manufacturing, process, yield, quality, and operations teams to understand workflows, pain points, data sources, and decision-making needs.
• Conduct deep operational assessments at manufacturing sites by observing workflows, interviewing frontline employees, supervisors, trainers, quality leaders, and operat ...
• Design, prototype, and productionize AI/ML solutions for manufacturing use cases, including visual inspection, defect classification, anomaly detection, predictive analytics, root-cause analysis, process optimization, and yield improvement.
• Translate business and manufacturing problems into technical solution designs, including data requirements, model approach, architecture, validation strategy, user interface needs, and deployment path.
• Work with structured and unstructured manufacturing data from databases, equipment logs, inspection systems, MES, yield systems, engineering reports, and other plant data sources.
• Communicate technical concepts clearly to both technical and non-technical stakeholders, including engineers, operators, managers, and senior leaders.
• Mentor local engineers and analysts on AI tools, data science methods, model interpretation, and practical AI adoption in manufacturing workflows.
• 5+ years of experience in data science, machine learning, AI engineering, manufacturing analytics, process engineering analytics, or a closely related technical field.
• Strong hands-on experience developing and deploying AI/ML models in real-world industrial or manufacturing environments.
• Practical experience using LLMs and generative AI tools for data analysis, workflow automation, knowledge retrieval, reporting, or engineering productivity applications.
• Strong programming skills in Python and common AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, OpenCV, and LangChain/LlamaIndex or similar frameworks.
• Experience working with relational databases and SQL, preferably including Oracle or other enterprise database systems.
• Ability to build end-to-end prototypes, including data extraction, model development, backend logic, simple user interfaces, dashboards, APIs, or workflow tools.
• Strong understanding of manufacturing data, process variation, yield analysis, quality systems, equipment data, inspection data, and root-cause analysis methods.
• English communication skills good enough to interact with US and Europe teams.
• Preferred Qualifications.
• Experience in semiconductor, photonics, electronics, optical components, precision manufacturing, or other high-volume advanced manufacturing environments.
• Experience with manufacturing systems such as MES, SPC, yield management systems, equipment automation systems, inspection platforms, or quality management systems.
• We are an equal opportunity employer and value diversity at our company.
• We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
• We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
• Please contact us to request accommodation.

ทักษะ:

Project Management, Problem Solving, Assembly, English, Thai

ประเภทงาน:

งานประจำ

• Ciena is seeking a.
• Process Engineer.
• to work within Site Engineering Operation group of Optical Component Organization. Working closely with our Design and NPI team and manufacturing partners. The Process Engineer shall be a part of transferring new products and work with the various parties to plan and action the transfer to our contract manufacturer (CM) and then lead in maintaining them in production.
• This position is located at our contract manufacturing partner site in Chonburi area. Specific responsibilities may include, but not limited to,.
• Process Engineering.
• Work with R&D and NPI team to define production requirements and specifications in terms of assembly process.
• Work with the combined team to develop and deliver training programs for CM operators and engineers.
• Work with the combined team to develop and maintain process and assembly tools in manufacture.
• Ensure device failure mode with significant failure rate are RCA.
• Propose and lead process improvement activities and bring up/install of expansion capital.
• Review and update PFMEA.
• This position requires a candidate with a strong, demonstrated record in the development and manufacture of Optical product.
• Skills and Experience.
• A minimum of a Bachelor's degree in a relevant discipline and 5+ years process experience in the design, manufacture of optical component assembly.
• Solid understanding of the principles and theory of optical devices such as lasers, modulators, detectors, and optical sub-assemblies.
• Strong knowledge and experience of the production processes related to the manufacture of optical component.
• Hands on experience of FiconTec machine.
• Excellent organisational and project management skills.
• Problem solving and the ability to solve technical issues in a high-pressure environment and resolve issues locally and remotely.
• Experience interacting with multi-functional, multi-locational teams.
• Good written and oral communication skills (English and Thai).
• At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard. Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination.
• Ciena is an Equal Opportunity Employer, including disability and protected veteran status.
• If contacted in relation to a job opportunity, please advise Ciena of any accommodation measures you may require.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Chemical Engineering, Product Development

ประเภทงาน:

งานประจำ

• Act as the primary technical contact for pulp & paper mills within the assigned territory.
• Provide on-site technical support for paper manufacturing processes, including stock preparation, wet end, press, dryer, and water systems.
• Troubleshoot paper machine performance issues using structured root cause analysis (e.g., runnability, deposits, breaks, quality variation).
• Optimize chemical programs such as Retention & Drainage, Strength Enhancement (dry & wet strength), Deposit, Pitch & Stickies Control, Defoamers & Foam Control and Microbiological Contro.
• Conduct system audits, machine surveys, and performance evaluations to improve productivity, efficiency, and paper quality.
• Lead product trials, start-ups, and scale-up activities at customer's site.
• Deliver technical training and application workshops for mill operators, engineers, and technical teams.
• Build strong working relationships with mill production managers, process engineers, and quality.
• Collaborate closely with Sales, Product Development, Quality, and Supply Chain teams.
• Prepare technical reports, monitor performance metrics, and identify continuous improvement opportunities.
• Bachelor's Degree in Chemical Engineering, Pulp & Paper Technology, Industrial Chemistry, Environmental Engineering, or a related field.
• Minimum 5 to 8 years of experience in technical service, process engineering, application engineering, production support, or customer-facing technical roles within the pulp & paper industry, specialty chemicals, water treatment, or related industrial process industries.
• Hands-on experience supporting paper manufacturing processes and chemical applications such as Retention & Drainage, Strength Enhancement, Deposit & Pitch Control, Stickies Control, Defoamer Programs, Microbiological Control, Process Water Treatment, and Boiler/Cooling Water Treatment is highly desirable.
• Strong understanding of paper machine operations, wet-end chemistry, process optimization, and troubleshooting of manufacturing challenges.
• Strong troubleshooting and analytical problem-solving skills.
• Ability to interpret process data and translate findings into practical solutions and customer value.
• Strong communication, presentation, and training skills.
• Willingness to travel regularly to customer sites across Thailand.
• Continuous professional development with many opportunities for growth.
• Access to a wide variety of internal and external training courses on our learning system.
• Hybrid working set-up.
• We understand that candidates will not meet every single desired job requirement. If your experience looks a little different from what we've identified and you think you can bring value to the role, we'd love to learn more about you.
• Be part of a high-growth company where your career can thrive.
• At Solenis, we understand that our greatest asset is our people. That is why we offer competitive compensation, and numerous opportunities for professional growth and development. So, if you are interested in working for a world-class company and enjoy solving complex challenges, consider joining our team.