project engineer (automation & communication)

ai/ml engineer

civil engineer

full-stack engineer – ai Jobs in Bahrain

full-stack engineer – ai

project engineer (automation & communication) Jobs in Bahrain

senior ai/ml engineer

full stack engineer ai

CALO

<div><h4 class="jobSectionHeader"><b>About Calo (more </b><b>here</b><b>)</b></h4><p>
Calo is an app providing personalized meal plans for busy people through nutritional algorithms, built with love by chefs, nutritionists, and software engineers.</p><p>
Launched in Bahrain in 2019, we have since expanded to 7 countries, delivered millions of meals to our customers, and are now expanding our mission of making healthy easy to retail and other verticals.</p><p>
We're on a noble mission to make healthy easy. We think this is one of the most important problems to tackle in our world today. We have global ambitions - no small thinking here.</p><h4 class="jobSectionHeader"><b>
Why This Role Matters</b></h4><p>
We are looking for a Full-stack Engineer &ndash; AI who will build and ship software using AI coding agents such as Codex and similar tools. You will develop applications for internal productivity and commercial products, leveraging AI-assisted development to accelerate engineering workflows.</p><p>
This role is ideal for engineers who are comfortable working with AI-driven coding environments, orchestrating coding agents, and building modern full-stack applications quickly and reliably.</p><p>
You will work across the entire product stack, from backend systems and APIs to user-facing interfaces, using AI as a core part of the development process.</p><h4 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h4><h5 class="jobSectionHeader"><b>
AI-Assisted Software Development</b></h5><ul><li><p>
Use coding agents (e.g., Codex and similar AI tools) to design, implement, and iterate on software systems.</p></li><li><p>
Build and deploy applications using AI-assisted development workflows.</p></li><li><p>
Design prompts, agent workflows, and automation pipelines that improve engineering velocity.</p></li></ul><h5 class="jobSectionHeader"><b>
Full-stack Development</b></h5><ul><li><p>
Develop scalable backend services and APIs.</p></li><li><p>
Build modern frontend interfaces and dashboards.</p></li><li><p>
Integrate internal tools and external services into production systems.</p></li></ul><h5 class="jobSectionHeader"><b>
AI Engineering Workflow</b></h5><ul><li><p>
Design and maintain agent-driven development processes.</p></li><li><p>
Evaluate and adopt emerging AI coding tools and frameworks.</p></li><li><p>
Optimize software delivery through automation and agent orchestration.</p></li></ul><h5 class="jobSectionHeader"><b>
Product Development</b></h5><ul><li><p>
Rapidly prototype and ship features.</p></li><li><p>
Collaborate with product teams to turn ideas into working software.</p></li><li><p>
Build tools that improve internal operations and developer productivity.</p></li></ul><h4 class="jobSectionHeader"><b>
What We&rsquo;re Looking For</b></h4><h4 class="jobSectionHeader"><b>
Requirements</b></h4><h5 class="jobSectionHeader"><b>
Experience</b></h5><ul><li><p>
1+ year of professional experience working with AI coding agents (Codex or similar).
</p></li><li><p>Experience building full-stack applications in production environments.</p></li></ul><h5 class="jobSectionHeader"><b>
Technical Skills</b></h5><p>
Strong experience with:</p><p><b>
Backend</b></p><ul><li><p>
Node.js / Python / Go / similar modern backend languages</p></li><li><p>
API design (REST / GraphQL)</p></li><li><p>
Databases (PostgreSQL, MongoDB, etc.)</p></li></ul><h6 class="jobSectionHeader"><b>
Frontend</b></h6><ul><li><p>
React / Next.js / modern frontend frameworks</p></li><li><p>
TypeScript / JavaScript</p></li></ul><h6 class="jobSectionHeader"><b>
AI Development</b></h6><ul><li><p>
Working with AI coding assistants or autonomous coding agents</p></li><li><p>
Prompt engineering for development workflows</p></li><li><p>
AI-assisted debugging, refactoring, and feature development</p></li></ul><h6 class="jobSectionHeader"><b>
Infrastructure</b></h6><ul><li><p>
Git</p></li><li><p>
Docker</p></li><li><p>
Cloud platforms (AWS / GCP / Azure)</p></li></ul><h5 class="jobSectionHeader"><b>
Preferred Qualifications</b></h5><ul><li><p>
Experience building agent-based development workflows.</p></li><li><p>
Familiarity with LLM APIs and AI tooling ecosystems.</p></li><li><p>
Experience building developer tools or internal automation systems.
</p></li><li><p>Startup or fast-paced product development experience.</p></li></ul><h4 class="jobSectionHeader"><b>
Who You Are</b></h4><ul><li><p>
An engineer who uses AI as a core part of how you build software.</p></li><li><p>
Strong problem-solver who can ship quickly while maintaining quality.</p></li><li><p>
A builder who enjoys experimenting with new AI-powered development paradigms.</p></li></ul><h4 class="jobSectionHeader"><b>
The Hiring Journey</b></h4><ul><li><p>
Screening with TA Partner (30 min)</p></li><li><p>
Technical Interview with the VP of AI (45 min)</p></li><li><p>
Culture Fit Interview with the Hiring and People Team Members (30 min)</p></li><li><p>
Offer</p></li></ul><h4 class="jobSectionHeader"><b>
Ready to Join?</b></h4><p>
If this role excites you, and you see yourself matching at least 85% of the criteria above, what are you waiting for? <b>Let&rsquo;s gooo!</b></p></div>

Full-stack Engineer – AI

Calo Inc.

<div>
 <strong>
  <strong>
   About Calo (more
  </strong>
  <strong>
   here
  </strong>
  <strong>
   )
  </strong>
 </strong>
 Calo is an app providing personalized meal plans for busy people through nutritional algorithms, built with love by chefs, nutritionists, and software engineers.
 <br/>
 <br/>
 Launched in Bahrain in 2019, we have since expanded to 7 countries, delivered millions of meals to our customers, and are now expanding our mission of making healthy easy to retail and other verticals.
 <br/>
 <br/>
 We're on a noble mission to make healthy easy. We think this is one of the most important problems to tackle in our world today. We have global ambitions - no small thinking here.
 <br/>
 <br/>
 <strong>
  <strong>
   Why This Role Matters
  </strong>
 </strong>
 We are looking for a Full-stack Engineer &ndash; AI who will build and ship software using AI coding agents such as Codex and similar tools. You will develop applications for internal productivity and commercial products, leveraging AI-assisted development to accelerate engineering workflows.
 <br/>
 <br/>
 This role is ideal for engineers who are comfortable working with AI-driven coding environments, orchestrating coding agents, and building modern full-stack applications quickly and reliably.
 <br/>
 <br/>
 You will work across the entire product stack, from backend systems and APIs to user-facing interfaces, using AI as a core part of the development process.
 <br/>
 <br/>
 <strong>
  <strong>
   What You&rsquo;ll Do
   <br/>
   <br/>
  </strong>
 </strong>
 <strong>
  AI-Assisted Software Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Use coding agents (e.g., Codex and similar AI tools) to design, implement, and iterate on software systems.
  </li>
  <li>
   Build and deploy applications using AI-assisted development workflows.
  </li>
  <li>
   Design prompts, agent workflows, and automation pipelines that improve engineering velocity.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Full-stack Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop scalable backend services and APIs.
  </li>
  <li>
   Build modern frontend interfaces and dashboards.
  </li>
  <li>
   Integrate internal tools and external services into production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  AI Engineering Workflow
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and maintain agent-driven development processes.
  </li>
  <li>
   Evaluate and adopt emerging AI coding tools and frameworks.
  </li>
  <li>
   Optimize software delivery through automation and agent orchestration.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Product Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Rapidly prototype and ship features.
  </li>
  <li>
   Collaborate with product teams to turn ideas into working software.
  </li>
  <li>
   Build tools that improve internal operations and developer productivity.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   What We&rsquo;re Looking For
   <br/>
   <br/>
  </strong>
 </strong>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <strong>
  <strong>
   Experience
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   1+ year of professional experience working with AI coding agents (Codex or similar).
  </li>
  <li>
   Experience building full-stack applications in production environments.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Technical Skills
  </strong>
 </strong>
 Strong experience with:
 <br/>
 <br/>
 <strong>
  Backend
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Node.js / Python / Go / similar modern backend languages
  </li>
  <li>
   API design (REST / GraphQL)
  </li>
  <li>
   Databases (PostgreSQL, MongoDB, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Frontend
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   React / Next.js / modern frontend frameworks
  </li>
  <li>
   TypeScript / JavaScript
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   AI Development
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Working with AI coding assistants or autonomous coding agents
  </li>
  <li>
   Prompt engineering for development workflows
  </li>
  <li>
   AI-assisted debugging, refactoring, and feature development
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Infrastructure
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Git
  </li>
  <li>
   Docker
  </li>
  <li>
   Cloud platforms (AWS / GCP / Azure)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience building agent-based development workflows.
  </li>
  <li>
   Familiarity with LLM APIs and AI tooling ecosystems.
  </li>
  <li>
   Experience building developer tools or internal automation systems.
  </li>
  <li>
   Startup or fast-paced product development experience.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Who You Are
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   An engineer who uses AI as a core part of how you build software.
  </li>
  <li>
   Strong problem-solver who can ship quickly while maintaining quality.
  </li>
  <li>
   A builder who enjoys experimenting with new AI-powered development paradigms.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   The Hiring Journey
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Screening with TA Partner (30 min)
  </li>
  <li>
   Technical Interview with the VP of AI (45 min)
  </li>
  <li>
   Culture Fit Interview with the Hiring and People Team Members (30 min)
  </li>
  <li>
   Offer
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Ready to Join?
  </strong>
 </strong>
 If this role excites you, and you see yourself matching at least 85% of the criteria above, what are you waiting for?
 <strong>
  Let&rsquo;s gooo! 🚀
 </strong>
</div>


VAM Systems Inc

<p><b>VAM Systems </b>is currently looking for <b>AI/ML Specialists (Data Scientists/ ML Engineer) </b>(On-Site) for our <b>Bahrain </b>operations with the following skillsets and terms &amp; conditions:</p><p><b>Years of Experience: 7 &ndash; 10 years</b></p><p><b>Qualification</b></p><p>Bachelor&rsquo;s Degree in Computer Science / Engineering<br/>Preferably BE Computer Science &amp; Engineering</p><p><b>Professional Training Required: </b>Machine Learning, Deep Learning, MLOps, AI in Financial Services.<br/><b>Professional Qualification Required: </b>Google Professional ML Engineer, Microsoft AI Engineer Associate Professional Licenses Required Not applicable.<br/><b>Professional Certifications Required: </b>TensorFlow Developer Certificate, AWS Certified Machine Learning.</p><p><b>Must-Have:</b></p><p><b>Proven hands-on delivery experience in banking, financial institutions, or insurance within Gen AI solutions such as chatbots, document analysis, etc., leveraging RAG and robust architecture with proper governance and security measures</b></p><p><b>Several years of ML experience with implemented use cases.</b><br/>Hands-on work experience most of which in banking, financial institutions, or insurance industries.</p><p><b>Experience required:</b></p><p>Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms.<br/>Experience with model evaluation and performance metrics.</p><p>Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering.<br/>Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management.<br/>Ability to communicate insights and build explainable AI models.</p><p><b>Job Responsibility:</b></p><p>Design and develop machine learning models to support AI-driven banking solutions Collaborate with data engineers to access and prepare data for modeling Apply statistical and ML techniques to solve business problems (e.g., churn prediction, credit scoring) Evaluate model performance and optimize for accuracy, precision, and recall Deploy models into production using MLOps frameworks and CI/CD pipelines Ensure models are explainable, auditable, and compliant with regulatory standards Work with business stakeholders to identify AI opportunities and define success metrics Document model assumptions, data sources, and performance benchmarks.</p><p><b>Core AI / NLP Engineering</b></p><ul><li>Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.)</li><li>LLM fine-tuning (LoRA, PEFT, prompt tuning)</li><li>Retrieval-Augmented Generation (RAG), vector databases (Pinecone, FAISS, Weaviate, Chroma)</li><li>Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)</li><li>Knowledge of embeddings, tokenization, and transformer architecture</li><li>Cloud AI tools: AWS Bedrock, Azure OpenAI, Vertex AI, OpenSearch, ElasticSearch</li></ul><p><b>Model evaluation: hallucination detection, grounding, and benchmarking (BLEU, ROUGE, TruthfulQA, etc.)</b></p><p><b>Software Engineering &amp; Backend Integration</b></p><p><b>RESTful and GraphQL APIs, webhooks</b></p><ul><li>Containerization and deployment (Docker, Kubernetes, CI/CD)</li><li>Authentication and user/session management</li><li>Data pipelines and microservices</li><li>Knowledge of frameworks like FastAPI, Flask, NestJS, or Express</li><li>Integration with enterprise data (SharePoint, Salesforce, SQL, internal APIs)</li></ul><p><b>Agent Orchestration &amp; Tooling </b></p><ul><li>LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks</li><li>Task-decomposition and reasoning chains</li><li>Function calling, tool use, and API chaining</li><li>Memory design (short-term vs long-term)</li><li>Context management and grounding strategies.</li></ul><p><b>Conversational UX / Design </b></p><ul><li>Conversation design frameworks (Google CCAI, Microsoft Bot Framework, Voiceflow, Botpress)</li><li>Flow design and intent management (Dialogflow, Rasa, Cognigy)</li><li>Tone, empathy, and personality design for AI personas</li><li>A/B testing dialogue variants and measuring user satisfaction.</li></ul><p><b>Data &amp; Infrastructure </b></p><p><b>Data pipelines (Airflow, dbt, Kafka)</b></p><ul><li>Structured/unstructured data ingestion (PDFs, databases, APIs)</li><li>Feature store and model registry management (MLflow, Kubeflow)</li><li>Vector database deployment and optimization</li><li>Monitoring, logging, and drift detection.</li></ul><p><b>Governance, Security &amp; Compliance </b></p><ul><li>Model explainability (SHAP, LIME)</li><li>Bias/fairness audits and data privacy</li><li>Compliance with GDPR, ISO 42001, NIST AI RMF, and local banking regulations</li><li>Secure prompt logging and audit trails.</li></ul><p><b>Products &amp; Strategy </b></p><ul><li>Translating business problems into AI use cases</li><li>Roadmapping and budget planning</li><li>KPI design (accuracy, user satisfaction, automation ROI)</li><li>Vendor management (OpenAI, Anthropic, AWS, etc.)</li><li>Change management and user adoption</li></ul><p><b>Joining time frame: (15 - 30 days)</b></p><p>Job Type: Full-time</p>

AI/ML Specialists (Data Scientists/ ML Engineer)

Yokogawa

<div><div>Not just a job, but a career</div><div>
Yokogawa, award winner for &lsquo;Best Asset Monitoring Technology&rsquo; and &lsquo;Best Digital Twin Technology&rsquo; at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.</div><div></div><div>
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.</div><div></div><div>
About the Team<br>
Our 18,000 employees work in over 60 countries with one corporate mission, to &quot;co-innovate tomorrow&quot;. 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.</div><div></div><div>
Job Description</div><div>
We are looking for a Senior AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil &amp; 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.</div><div></div><div>
Job Overview</div><div></div><div>
You will be part of a Project Delivery team to:</div><ul><li>
Develop dynamic process simulation model to simulate various plant scenarios.</li><li>
Exploratory Data Analysis to analyze trends and patterns, data pre-processing and make intelligent recommendations.</li><li>
Implement classical machine learning techniques to prepare soft sensors, reinforcement learning models for process plant autonomous control operations.</li><li>
Design and develop AI models that troubleshoot the plant upsets, support asset performance management across various maintenance strategies.</li><li>
Leverage Generative AI (Large Language Models, Deep Reinforcement Learning) to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior.</li><li>
Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, Historians, EAM, MES/MOM, SCM, and ERP systems.</li><li>
Ensure compliance with ethical AI principles, particularly in terms of fairness, transparency, and bias mitigation.</li></ul><div></div><div>
Key Responsibilities</div><div></div><div>
Technical Leadership &amp; Mentorship</div><ul><li>
A.I. project implementation from data ingestion and feature engineering to model deployment and monitoring.</li><li>
Lead and mentor a team of process engineers and machine learning engineers.</li><li>
Review the process model and guide the team to develop plant scenarios in the dynamic simulation model accurately.</li><li>
Advocate best practices in Data analysis, Data pre-processing and machine learning model development.</li></ul><div></div><div>
Stakeholder Collaboration &amp; Communication</div><ul><li>
Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI-driven solutions.</li><li>
Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.</li></ul><div></div><div>
Compliance &amp; Risk Management</div><ul><li>
Ensure all AI/ML solutions comply with industry regulations, safety standards, and data governance policies.</li><li>
Proactively address potential risks related to data privacy, model bias, and operational safety.</li></ul><div></div><div>
Requirements</div><ul><li>
Bachelor&rsquo;s/master&rsquo;s in chemical engineering, AI, Machine Learning, or related field.</li><li>
10+ years of hands-on experience in AI/ML, with at least 4 years in a senior or lead role.</li><li>
Proven project delivery experience in industrial or energy sectors, with a preference for oil &amp; gas.</li><li>
Demonstrated knowledge of oil &amp; gas processes (upstream, midstream, downstream), instrumentation, and control systems.</li><li>
Proven Expertise to develop process dynamic simulations using PFDs and P&amp;IDs and trouble shooting.</li><li>
Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.</li><li>
Familiarity with real-time data challenges and solutions specific to high-stakes industrial environments.</li><li>
Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.</li><li>
Strong experience with classical machine learning, deep learning and reinforcement learning projects.</li><li>
Identify relevant metrics for A.I. model evaluation and Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.</li><li>
Proven experience in Generative AI, RAG and vector embeddings for optimized knowledge retrieval and decision-making, and multi-agent systems for industrial applications.</li><li>
Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making.</li><li>
Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.</li></ul><div></div><div>
Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job)</div><div>
Programming &amp; Frameworks</div><ul><li>
Languages: Proficiency in Python and visual basic coding is essential.</li><li>
ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras.</li></ul><div></div><div>
Data Engineering &amp; Integration</div><ul><li>
Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.</li></ul><div></div><div>
Personal Attributes (Special personal characteristics/ interpersonal skills)</div><ul><li>
Consistently demonstrates exceptional technical skills, competence, and productivity.</li><li>
Deeply passionate about transforming emerging technologies into practical, industrial solutions.</li><li>
Possesses excellent communication and interpersonal abilities.</li><li>
A fast learner with a strong aptitude for collaboration and teamwork.</li></ul><div></div><div>
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.</div><div></div><div>
Are you being referred to one of our roles? If so, ask your connection at Yokogawa<br>
about our Employee Referral process!</div></div>

Senior AI/ML Engineer

<div>
 <strong>
  Not just a job, but a career
  <br/>
  <br/>
 </strong>
 Yokogawa, award winner for &lsquo;Best Asset Monitoring Technology&rsquo; and &lsquo;Best Digital Twin Technology&rsquo; at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <strong>
  About The Team
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 We are looking for a Senior AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil &amp; 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.
 <br/>
 <br/>
 <strong>
  Job Overview
  <br/>
  <br/>
 </strong>
 You will be part of a Project Delivery team to:
 <br/>
 <br/>
 <ul>
  <li>
   Develop dynamic process simulation model to simulate various plant scenarios.
  </li>
  <li>
   Exploratory Data Analysis to analyze trends and patterns, data pre-processing and make intelligent recommendations.
  </li>
  <li>
   Implement classical machine learning techniques to prepare soft sensors, reinforcement learning models for process plant autonomous control operations.
  </li>
  <li>
   Design and develop AI models that troubleshoot the plant upsets, support asset performance management across various maintenance strategies.
  </li>
  <li>
   Leverage Generative AI (Large Language Models, Deep Reinforcement Learning) to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior.
  </li>
  <li>
   Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, Historians, EAM, MES/MOM, SCM, and ERP systems.
  </li>
  <li>
   Ensure compliance with ethical AI principles, particularly in terms of fairness, transparency, and bias mitigation.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Technical Leadership &amp; Mentorship
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   A.I. project implementation from data ingestion and feature engineering to model deployment and monitoring.
  </li>
  <li>
   Lead and mentor a team of process engineers and machine learning engineers.
  </li>
  <li>
   Review the process model and guide the team to develop plant scenarios in the dynamic simulation model accurately.
  </li>
  <li>
   Advocate best practices in Data analysis, Data pre-processing and machine learning model development.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Stakeholder Collaboration &amp; Communication
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI-driven solutions.
  </li>
  <li>
   Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compliance &amp; Risk Management
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Ensure all AI/ML solutions comply with industry regulations, safety standards, and data governance policies.
  </li>
  <li>
   Proactively address potential risks related to data privacy, model bias, and operational safety.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s/master&rsquo;s in chemical engineering, AI, Machine Learning, or related field.
  </li>
  <li>
   10+ years of hands-on experience in AI/ML, with at least 4 years in a senior or lead role.
  </li>
  <li>
   Proven project delivery experience in industrial or energy sectors, with a preference for oil &amp; gas.
  </li>
  <li>
   Demonstrated knowledge of oil &amp; gas processes (upstream, midstream, downstream), instrumentation, and control systems.
  </li>
  <li>
   Proven Expertise to develop process dynamic simulations using PFDs and P&amp;IDs and trouble shooting.
  </li>
  <li>
   Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.
  </li>
  <li>
   Familiarity with real-time data challenges and solutions specific to high-stakes industrial environments.
  </li>
  <li>
   Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.
  </li>
  <li>
   Strong experience with classical machine learning, deep learning and reinforcement learning projects.
  </li>
  <li>
   Identify relevant metrics for A.I. model evaluation and Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.
  </li>
  <li>
   Proven experience in Generative AI, RAG and vector embeddings for optimized knowledge retrieval and decision-making, and multi-agent systems for industrial applications.
  </li>
  <li>
   Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making.
  </li>
  <li>
   Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job)
  <br/>
  <br/>
 </strong>
 <strong>
  Programming &amp; Frameworks
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Languages: Proficiency in Python and visual basic coding is essential.
  </li>
  <li>
   ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Engineering &amp; Integration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Personal Attributes (Special Personal Characteristics/ Interpersonal Skills)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Consistently demonstrates exceptional technical skills, competence, and productivity.
  </li>
  <li>
   Deeply passionate about transforming emerging technologies into practical, industrial solutions.
  </li>
  <li>
   Possesses excellent communication and interpersonal abilities.
  </li>
  <li>
   A fast learner with a strong aptitude for collaboration and teamwork.
   <br/>
   <br/>
  </li>
 </ul>
 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.
 <br/>
 <br/>
 Are you being referred to one of our roles? If so, ask your connection at Yokogawa
 <br/>
 <br/>
 about our Employee Referral process!
</div>


<div><div>Not just a job, but a career</div><div>
Yokogawa, award winner for &lsquo;Best Asset Monitoring Technology&rsquo; and &lsquo;Best Digital Twin Technology&rsquo; at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.</div><div></div><div>
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.</div><div></div><div>
About the Team<br>
Our 18,000 employees work in over 60 countries with one corporate mission, to &quot;co-innovate tomorrow&quot;. 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.</div><div></div><div>
Job Description</div><div></div><div>
We are looking for an AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil &amp; gas industry. In this role, you will take part in 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.</div><div></div><div>
Job Overview</div><div></div><div>
You will be part of a Project Delivery team to:</div><ul><li>
Develop dynamic process simulation model to simulate various plant scenarios.</li><li>
Exploratory Data Analysis to analyze trends and patterns, data pre-processing and make intelligent recommendations.</li><li>
Implement classical machine learning techniques to prepare soft sensors, reinforcement learning models for process plant autonomous control operations.</li><li>
Design and develop AI models that troubleshoot the plant upsets, support asset performance management across various maintenance strategies.</li><li>
Leverage Generative AI (Large Language Models, Deep Reinforcement Learning) to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior.</li><li>
Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, Historians, EAM, MES/MOM, SCM, and ERP systems.</li><li>
Ensure compliance with ethical AI principles, particularly in terms of fairness, transparency, and bias mitigation.</li></ul><div></div><div>
Key Responsibilities</div><div></div><div>
Technical Leadership &amp; Mentorship</div><ul><li>
Develop dynamic process simulation model for various plant scenarios accurately.</li><li>
Analyze data historian, exploratory data analysis and data pre-processing.</li><li>
A.I. project implementation from data ingestion and feature engineering to model deployment and monitoring.</li><li>
Advocate best practices in Data analysis, Data pre-processing and machine learning model development.</li></ul><div></div><div>
Stakeholder Collaboration &amp; Communication</div><ul><li>
Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI-driven solutions.</li><li>
Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.</li></ul><div></div><div>
Requirements</div><ul><li>
Bachelor&rsquo;s/master&rsquo;s in chemical engineering, AI, Machine Learning, or related field.</li><li>
6+ years of hands-on experience in AI/ML and process simulations projects execution.</li><li>
Proven project delivery experience in industrial or energy sectors, with a preference for oil &amp; gas.</li><li>
Demonstrated knowledge of oil &amp; gas processes (upstream, midstream, downstream), instrumentation, and control systems.</li><li>
Proven Expertise to develop process dynamic simulations using PFDs and P&amp;IDs and trouble shooting.</li><li>
Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.</li><li>
Familiarity with real-time data challenges and solutions specific to high-stakes industrial environments.</li><li>
Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.</li><li>
Strong experience with classical machine learning, deep learning and reinforcement learning projects.</li><li>
Identify relevant metrics for A.I. model evaluation and Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.</li><li>
Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.</li></ul><div></div><div>
Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job)</div><div>
Programming &amp; Frameworks</div><ul><li>
Languages: Proficiency in Python and visual basic coding is essential.</li><li>
ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras.</li></ul><div></div><div>
Data Engineering &amp; Integration</div><ul><li>
Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.</li></ul><div></div><div>
Personal Attributes (Special personal characteristics/ interpersonal skills)</div><ul><li>
Consistently demonstrates exceptional technical skills, competence, and productivity.</li><li>
Deeply passionate about transforming emerging technologies into practical, industrial solutions.</li><li>
Possesses excellent communication and interpersonal abilities.</li><li>
A fast learner with a strong aptitude for collaboration and teamwork.</li></ul><div></div><div>
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.</div><div></div><div>
Are you being referred to one of our roles? If so, ask your connection at Yokogawa<br>
about our Employee Referral process!</div></div>

AI/ML Engineer

<div>
 <strong>
  Not just a job, but a career
  <br/>
  <br/>
 </strong>
 Yokogawa, award winner for &lsquo;Best Asset Monitoring Technology&rsquo; and &lsquo;Best Digital Twin Technology&rsquo; at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <strong>
  About The Team
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 We are looking for an AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil &amp; gas industry. In this role, you will take part in 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.
 <br/>
 <br/>
 <strong>
  Job Overview
  <br/>
  <br/>
 </strong>
 You will be part of a Project Delivery team to:
 <br/>
 <br/>
 <ul>
  <li>
   Develop dynamic process simulation model to simulate various plant scenarios.
  </li>
  <li>
   Exploratory Data Analysis to analyze trends and patterns, data pre-processing and make intelligent recommendations.
  </li>
  <li>
   Implement classical machine learning techniques to prepare soft sensors, reinforcement learning models for process plant autonomous control operations.
  </li>
  <li>
   Design and develop AI models that troubleshoot the plant upsets, support asset performance management across various maintenance strategies.
  </li>
  <li>
   Leverage Generative AI (Large Language Models, Deep Reinforcement Learning) to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior.
  </li>
  <li>
   Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, Historians, EAM, MES/MOM, SCM, and ERP systems.
  </li>
  <li>
   Ensure compliance with ethical AI principles, particularly in terms of fairness, transparency, and bias mitigation.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Technical Leadership &amp; Mentorship
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop dynamic process simulation model for various plant scenarios accurately.
  </li>
  <li>
   Analyze data historian, exploratory data analysis and data pre-processing.
  </li>
  <li>
   A.I. project implementation from data ingestion and feature engineering to model deployment and monitoring.
  </li>
  <li>
   Advocate best practices in Data analysis, Data pre-processing and machine learning model development.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Stakeholder Collaboration &amp; Communication
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Partner with domain experts, process engineers, and project managers to translate complex operational challenges into AI-driven solutions.
  </li>
  <li>
   Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s/master&rsquo;s in chemical engineering, AI, Machine Learning, or related field.
  </li>
  <li>
   6+ years of hands-on experience in AI/ML and process simulations projects execution.
  </li>
  <li>
   Proven project delivery experience in industrial or energy sectors, with a preference for oil &amp; gas.
  </li>
  <li>
   Demonstrated knowledge of oil &amp; gas processes (upstream, midstream, downstream), instrumentation, and control systems.
  </li>
  <li>
   Proven Expertise to develop process dynamic simulations using PFDs and P&amp;IDs and trouble shooting.
  </li>
  <li>
   Proficiency in handling large-scale data, time-series data, and sensor/IoT data within industrial contexts.
  </li>
  <li>
   Familiarity with real-time data challenges and solutions specific to high-stakes industrial environments.
  </li>
  <li>
   Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.
  </li>
  <li>
   Strong experience with classical machine learning, deep learning and reinforcement learning projects.
  </li>
  <li>
   Identify relevant metrics for A.I. model evaluation and Present technical outcomes to both technical and non-technical audiences, highlighting business value and ROI.
  </li>
  <li>
   Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Knowledge/ Professional Skills (Technical knowledge or skills required to perform the job)
  <br/>
  <br/>
 </strong>
 <strong>
  Programming &amp; Frameworks
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Languages: Proficiency in Python and visual basic coding is essential.
  </li>
  <li>
   ML Libraries: Expert-level knowledge of Numpy, Pandas, Scikit-learn, TensorFlow, and Keras.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Engineering &amp; Integration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Personal Attributes (Special Personal Characteristics/ Interpersonal Skills)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Consistently demonstrates exceptional technical skills, competence, and productivity.
  </li>
  <li>
   Deeply passionate about transforming emerging technologies into practical, industrial solutions.
  </li>
  <li>
   Possesses excellent communication and interpersonal abilities.
  </li>
  <li>
   A fast learner with a strong aptitude for collaboration and teamwork.
   <br/>
   <br/>
  </li>
 </ul>
 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.
 <br/>
 <br/>
 Are you being referred to one of our roles? If so, ask your connection at Yokogawa
 <br/>
 <br/>
 about our Employee Referral process!
</div>


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