Time since we first saw it
Day 58
Similar jobs usually come down between day 6 and day 70.
From 4,452 similar postings that came down. Coming down is not always a hire.
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Develop dynamic process simulation models of plant scenarios
Build soft sensors and reinforcement learning models for plant control
Design AI models to troubleshoot plant upsets and support asset performance
Lead and mentor process engineers and machine learning engineers
Deploy AI models into PLC, DCS, SCADA and ERP industrial systems
Develop dynamic process simulation model to simulate various plant scenarios.
Implement classical machine learning techniques to prepare soft sensors, reinforcement learning models for process plant autonomous control operations.
Design and develop AI models that troubleshoot the plant upsets, support asset performance management across various maintenance strategies.
Lead and mentor a team of process engineers and machine learning engineers.
Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, Historians, EAM, MES/MOM, SCM, and ERP systems.
Bachelor’s/master’s in chemical engineering, AI, Machine Learning, or related field.
Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.
10+ years of hands-on experience in AI/ML, with at least 4 years in a senior or lead role.
Demonstrated knowledge of oil & gas processes (upstream, midstream, downstream), instrumentation, and control systems.
Proven Expertise to develop process dynamic simulations using PFDs and P&IDs and trouble shooting.
Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.
Requirements - Bachelor’s/master’s in chemical engineering, AI, Machine Learning, or related field. - 10+ years of hands-on experience in AI/ML, with at least 4 years in a senior or lead role.
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Day 58
Similar jobs usually come down between day 6 and day 70.
From 4,452 similar postings that came down. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Programming & Frameworks - Languages: Proficiency in Python and visual basic coding is essential. - ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras.
- Proven experience in Generative AI, RAG and vector embeddings for optimized knowledge retrieval and decision-making, and multi-agent systems for industrial applications. - Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making. - Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.
- Languages: Proficiency in Python and visual basic coding is essential. - ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras. Data Engineering & Integration
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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
We are looking for a Senior AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil & gas industry. In this role, you will drive the design, development, and implementation of advanced AI/ML models, working closely with cross-functional teams to optimize operations and deliver data-driven insights in challenging industrial environments.
Job Overview
You will be part of a Project Delivery team to:
Key Responsibilities
Technical Leadership & Mentorship
Stakeholder Collaboration & Communication
Compliance & Risk Management
Requirements
Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job)
Programming & Frameworks
Data Engineering & Integration
Personal Attributes (Special personal characteristics/ interpersonal skills)
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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