Time since we first saw it
Day 49
Similar jobs usually come down between day 6 and day 70.
From 4,442 similar postings that came down. Coming down is not always a hire.
Reads like a ML Engineer role: putting models into production.
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Develop and deploy RAG systems, knowledge graphs and semantic search for engineering insights
Build intelligent agents that interact with enterprise systems, databases and digital twins
Apply machine learning to predictive maintenance, anomaly detection and process optimization
Build data pipelines that clean and contextualize structured and unstructured industrial data
Design, evaluate and deploy AI solutions from concept to production with global teams
Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions
Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools
Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization
Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data
Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment
· Experience in real-world data science projects, internships, hackathons, and personal projects · Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn, matplotlib, and seaborn · Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI
· Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI · Familiar with databases (e.g., PostgreSQL, Minio) and SQL for data storage and retrieval By responding to Yokogawa’s advertisement, consent is considered given to Yokogawa to collect the required personal data for the purpose of recruitment with expectation that Yokogawa will protect personal data with security safeguards that are reasonable and appropriate to the sensitivity of the personal data, to protect it from unauthorized access, use or disclosure and complies with applicable regulatory requirements with respect to the retention of personal data.
· Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn, matplotlib, and seaborn · Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI · Familiar with databases (e.g., PostgreSQL, Minio) and SQL for data storage and retrieval
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 49
Similar jobs usually come down between day 6 and day 70.
From 4,442 similar postings that came down. Coming down is not always a hire.
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordCheck the employer’s posting for the current role and application details.
Already applied? Track this application
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Not just a job, but a career
Yokogawa, award winner for ‘Best Asset Monitoring Technology’ and ‘Best Digital Twin Technology’ at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.
Our aim is to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by utilizing our ability to measure and connect.
About the Team
Our 18,000 employees work in over 60 countries with one corporate mission, to "co-innovate tomorrow". We are looking for dynamic colleagues who share our passion for technology and care for our planet. In return, we offer you great career opportunities to grow yourself in a truly global culture where respect, value creation, collaboration, integrity, and gratitude are highly valued and exhibited in everything we do.
Job Description:
· Research and develop innovative LLM, Generative AI, and Agentic AI solutions for chemical and process industry applications
· Design and build AI-powered applications that leverage plant data, engineering knowledge, maintenance records, and operational documentation to improve decision making
· Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions to enable contextualized engineering insights
· Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools to automate workflows and support operations
· Develop scalable, reliable, and secure AI solutions, ensuring effective deployment, monitoring, maintenance, and continuous improvement in production environments
· Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization, and asset performance
· Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data
· Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment
· Automate engineering and business processes using AI, APIs, scripting, and open-source technologies to improve efficiency, scalability, and knowledge management
· Stay current with advancements in LLMs, Agentic AI, machine learning, industrial AI, and emerging technologies, continuously contributing new ideas and innovations to the organization
Job Requirements:
· Masters/Degree in Engineering/Sciences
· 3-6 years of relevant experience
· Experience with knowledge graphs, semantic search, industrial digital twins, or engineering knowledge management systems.
· Experience applying AI to plant operations, sustainability, energy optimization, asset performance management, or process safety use cases.
· Familiarity with Responsible AI, AI governance, cybersecurity, and human-in-the-loop decision-support systems.
· Experience in real-world data science projects, internships, hackathons, and personal projects
· Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn, matplotlib, and seaborn
· Proficient in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI
· Familiar with databases (e.g., PostgreSQL, Minio) and SQL for data storage and retrieval
By responding to Yokogawa’s advertisement, consent is considered given to Yokogawa to collect the required personal data for the purpose of recruitment with expectation that Yokogawa will protect personal data with security safeguards that are reasonable and appropriate to the sensitivity of the personal data, to protect it from unauthorized access, use or disclosure and complies with applicable regulatory requirements with respect to the retention of personal data.
We regret to inform that only shortlisted candidates will be notified.
Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture. We will actively recruit, develop, and promote people from a variety of backgrounds whodiffer in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status. We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances. Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential.
Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture. We will actively recruit, develop, and promote people from a variety of backgrounds who differ in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status. We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances. Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential.
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