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machine learning engineer

B&B Hotel Hannover-City

Are you passionate about combining machine learning and physics to accelerate simulation and optimization in energy systems? This is an exciting opportunity to join one of our major global clients as a Machine Learning Engineer &ndash; Physics-Based Surrogate Modelling, where you will design and deploy Graph Neural Network (GNN) and physics-informed neural network (PINN) models to emulate complex physical simulations for pipeline and well network systems.The role focuses on developing scalable surrogate models that capture multi-physics flow dynamics, reduce simulation costs, and enhance production optimization workflows. You will work at the intersection of data science, physics, and software engineering, transforming simulation data into actionable machine learning frameworks for predictive performance and real-time decision support.Key Responsibilities<ul><li>Develop, train, and deploy Graph Neural Network (GNN)-based surrogate models to approximate physics-based simulations for pipeline and well networks.</li><li>Design data transformation pipelines to convert numerical simulation outputs into graph representations suitable for deep learning architectures.</li><li>Integrate physics constraints and governing equations into neural network loss functions to ensure physically consistent predictions.</li><li>Implement Physics-Informed Neural Networks (PINNs) and hybrid ML-physics models for flow dynamics and pressure prediction.</li><li>Collaborate with domain experts to interpret simulation data, validate model outputs, and ensure consistency with reservoir and production physics.</li><li>Optimize model training for scalability, accuracy, and generalization across varying simulation conditions.</li><li>Build and automate model evaluation, versioning, and deployment frameworks using MLOps tools.</li><li>Develop visualization and post-processing tools to analyze surrogate model behavior and compare results with high-fidelity simulators.</li><li>Document methodologies, validation reports, and research findings for knowledge transfer and technical review.</li><li>Stay current with emerging trends in scientific machine learning, GNNs, and physics-informed AI frameworks.</li></ul>Required Qualifications / Experience / Skills<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Applied Mathematics, Petroleum Engineering, Mechanical Engineering, or a related field (Ph.D. preferred).</li><li>Minimum 7+ years of experience in machine learning model development, with focus on physics-based or scientific ML applications.</li><li>Proven expertise in Graph Neural Networks (GNNs) using frameworks such as PyTorch Geometric, DGL, or DeepMind Graph Nets.</li><li>Experience developing Physics-Informed Neural Networks (PINNs) or hybrid ML models incorporating domain constraints.</li><li>Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).</li><li>Solid understanding of numerical simulation, PDEs, and fluid dynamics in pipeline or reservoir systems.</li><li>Familiarity with data preprocessing, feature engineering, and large-scale scientific data handling.</li><li>Hands-on experience with MLOps tools (MLflow, Docker, Git, CI/CD pipelines) for model deployment and version control.</li><li>Ability to work cross-functionally with simulation engineers, data scientists, and domain specialists.</li><li>Strong analytical, mathematical modeling, and problem-solving skills with attention to detail.</li><li>Excellent written and verbal communication skills for technical documentation and presentations.</li></ul>Job Location 100% Remote / HybridType of Employment Full-time / PermanentSalary: NegotiableWhat You Can Expect from the Employer<ul><li>Opportunity to work with a global leader in energy and simulation technology.</li><li>Exposure to cutting-edge AI research and scientific computing.</li><li>Competitive compensation and benefits package.</li><li>Collaborative and innovation-driven environment with professional growth opportunities.</li></ul>Job Types: Full-time, PermanentApplication Question(s):<ul><li>Do you have 7 or more years of experience developing deep learning or physics-based ML models?</li><li>Have you built or deployed Graph Neural Network (GNN) or Physics-Informed Neural Network (PINN) models in production or research settings?</li><li>Are you proficient in Python and experienced with frameworks such as PyTorch Geometric or DGL for physics-based modeling?</li></ul>

Machine Learning Engineer – Physics-Based Surrogate Modelling

Onliest

Job Title: Machine Learning Engineer &ndash; 3D GraphicsLocation: UAE Experience: 6+ years Job Type: Full-TimeRole: We are seeking a highly skilled and innovative Machine Learning Engineer with 3D Graphics expertise. In this role, you will be responsible for developing and optimizing 3D mannequin models using machine learning algorithms, computer vision techniques, and 3D rendering tools. You will collaborate with backend developers, data scientists, and UI/UX designers to create realistic, scalable, and interactive 3D visualization modules that enhance the user experience.Key Responsibilities:3D Mannequin Model Development:<ul><li>Design and develop 3D mannequin models using ML-based body shape estimation.</li><li>Implement pose estimation, texture mapping, and deformation models.</li><li>Use ML algorithms to adjust measurements for accurate sizing and fit.</li></ul>Machine Learning &amp; Computer Vision:<ul><li>Develop and fine-tune ML models for body shape recognition, segmentation, and fitting.</li><li>Implement pose detection algorithms using TensorFlow, PyTorch, or OpenCV.</li><li>Use GANs or CNNs for realistic 3D texture generation.</li></ul>3D Graphics &amp; Visualization:<ul><li>Create interactive 3D rendering pipelines using Three.js, Babylon.js, or Unity.</li><li>Optimize mesh processing, lighting, and shading for real-time rendering.</li><li>Use GPU-accelerated techniques for rendering efficiency.</li></ul>Model Optimization &amp; Performance:<ul><li>Optimize inference pipelines for faster real-time rendering.</li><li>Implement multi-threading and parallel processing for high performance.</li><li>Utilize cloud infrastructure (AWS/GCP) for distributed model training and inference.</li></ul>Collaboration &amp; Documentation:<ul><li>Collaborate with UI/UX designers for seamless integration of 3D models into web and mobile apps.</li><li>Maintain detailed documentation for model architecture, training processes, and rendering techniques.</li></ul>Key Skills &amp; Qualifications:Experience:<ul><li>3&ndash;8 years in Machine Learning, Computer Vision, and 3D Graphics Development.</li></ul>Technical Skills:<ul><li>Proficiency in Django, Python, TensorFlow, PyTorch, and OpenCV.</li><li>Strong expertise in 3D rendering frameworks: Three.js, Babylon.js, or Unity.</li><li>Experience with 3D model formats (GLTF, OBJ, FBX).</li><li>Familiarity with Mesh Recovery, PyMAF, and SMPL models.</li></ul>ML &amp; Data Skills:<ul><li>Hands-on experience with GANs, CNNs, and RNNs for texture and pattern generation.</li><li>Experience with 3D pose estimation and body measurement algorithms.</li></ul>Cloud &amp; Infrastructure:<ul><li>Experience with AWS (SageMaker, Lambda) or GCP (Vertex AI, Cloud Run).</li><li>Knowledge of Docker and Kubernetes for model deployment.</li></ul>Graphics &amp; Visualization:<ul><li>Knowledge of 3D rendering engines with shader programming.</li><li>Experience in optimization techniques for rendering large 3D models.</li></ul>Soft Skills:<ul><li>Strong problem-solving skills and attention to detail.</li><li>Excellent collaboration and communication skills.</li></ul>Interested candidates can send their updated resume to: careers@onliestworld.comJob Type: Full-time

ML Engineer -3D Graphic

GSSTech Group

<div>We are seeking a highly skilled and experienced Principal Data Scientist / IT Engineer (Applications) to lead data-driven initiatives and drive innovation across our organization. The ideal candidate will have a strong background in data science, machine learning, and cloud-based analytics, with the ability to translate complex business problems into actionable insights.
Requirements<h3 class="jobSectionHeader">
Key Responsibilities:</h3><ul>
<li>Analyze large and complex datasets to identify trends, patterns, and business opportunities.
</li><li>Develop, train, and deploy machine learning models for classification, regression, clustering, and recommendation systems.
</li><li>Collaborate with cross-functional teams to define business challenges and design end-to-end data science solutions.
</li><li>Communicate findings and insights through effective visualizations, dashboards, and presentations.
</li><li>Implement MLOps best practices for model deployment, monitoring, and optimization.
</li><li>Stay current with emerging technologies and advancements in data science, AI, and analytics.
</li><li>Ensure scalability and performance of models in production environments.
</li></ul><h3 class="jobSectionHeader">Required Skills &amp; Qualifications:</h3><ul>
<li>Proven experience in data science, machine learning, and advanced analytics.
</li><li>Strong programming skills in Python, R, or Scala.
</li><li>Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
</li><li>Familiarity with big data frameworks (e.g., Spark, Hadoop).
</li><li>Solid understanding of statistical analysis, predictive modeling, and data engineering workflows.
</li><li>Experience with MLOps, CI/CD pipelines, and deployment frameworks.
</li><li>Excellent communication and problem-solving skills.
</li><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Engineering, or a related field.
</li></ul><h3 class="jobSectionHeader">Preferred Qualifications:</h3><ul>
<li>Experience working in large-scale enterprise environments.
</li><li>Knowledge of data visualization tools such as Power BI, Tableau, or Looker.
</li><li>Experience leading or mentoring junior data scientists or engineers.</li></ul></div>

Principal Data Scientist - IT Applications

DarGlobal

<div>
 
 We are seeking an innovative
 
 AI Engineer / Data Scientist
 
 to lead the development and implementation of
 
 AI-driven tools and systems across the enterprise
 
 . The ideal candidate will combine deep technical expertise in
 
 machine learning, large language models (LLMs), and data analytics
 
 with a strategic understanding of how to embed AI capabilities within business processes.
 
 
 This role will drive the adoption of AI technologies across departments&mdash;enabling automation, improving decision-making, and fostering a data-first culture throughout the organization.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 Enterprise AI Implementation
 
 
 <ul>
 <li>
 Lead the design, development, and deployment of
 
 AI and automation tools
 
 across multiple business functions (marketing, sales, finance, operations, and customer experience).
 </li>
 <li>
 Collaborate with stakeholders to identify
 
 high-impact AI opportunities
 
 and develop scalable solutions.
 </li>
 <li>
 Build and manage
 
 AI platforms and internal tools
 
 that enhance productivity and decision-making across teams.
 </li>
 <li>
 Integrate AI capabilities (e.g., LLM-based assistants, chatbots, predictive analytics, generative content tools) into existing enterprise systems such as
 
 CRM, ERP, and data platforms
 
 .
 </li>
 <li>
 Establish
 
 best practices for AI governance, model lifecycle management, and ethical AI usage
 
 across the organization.
 </li>
 </ul>
 
 
 AI &amp; Machine Learning Development
 
 
 <ul>
 <li>
 Research, build, and deploy models for
 
 predictive analytics, natural language processing (NLP), computer vision, and recommendation systems
 
 .
 </li>
 <li>
 Develop APIs and microservices to operationalize ML models within production environments.
 </li>
 <li>
 Ensure solutions are
 
 scalable, secure, and compliant
 
 with enterprise data policies.
 </li>
 </ul>
 
 
 Data Science &amp; Analytics
 
 
 <ul>
 <li>
 Lead efforts in
 
 data collection, transformation, and feature engineering
 
 to support analytical models.
 </li>
 <li>
 Create
 
 dashboards and AI-powered insights tools
 
 to enable real-time decision support for leadership teams.
 </li>
 <li>
 Work with data engineering teams to maintain
 
 clean, consistent, and high-quality data pipelines
 
 .
 </li>
 </ul>
 
 
 Cross-Functional Collaboration
 
 
 <ul>
 <li>
 Partner with IT, digital transformation, and business units to align AI initiatives with enterprise goals.
 </li>
 <li>
 Conduct workshops and training to
 
 build AI literacy
 
 and encourage adoption across non-technical departments.
 </li>
 <li>
 Communicate insights and technical findings clearly to stakeholders at all levels.
 </li>
 </ul>
 
 
 Research &amp; Innovation
 
 
 <ul>
 <li>
 Continuously evaluate and implement the latest
 
 AI and automation platforms
 
 (e.g., OpenAI, Anthropic, Azure AI, Hugging Face, DataRobot).
 </li>
 <li>
 Explore opportunities for
 
 AI-driven business process reengineering
 
 and new product innovation.
 </li>
 <li>
 Stay ahead of trends in
 
 LLMs, multimodal AI, generative AI, and cognitive automation
 
 .
 </li>
 </ul>
 
 
 
 
 
 Education
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s in
 
 Computer Science, Artificial Intelligence, Data Science, or related fields
 
 .
 </li>
 <li>
 PhD preferred but not required.
 </li>
 </ul>
 
 
 
 
 
 Technical Skills
 
 
 <ul>
 <li>
 Strong proficiency in
 
 Python
 
 (pandas, NumPy, scikit-learn, PyTorch, TensorFlow).
 </li>
 <li>
 Experience implementing enterprise AI solutions using
 
 OpenAI API, LangChain, Azure AI, Hugging Face, or similar frameworks
 
 .
 </li>
 <li>
 Expertise in
 
 machine learning deployment
 
 and
 
 MLOps
 
 (Docker, MLflow, CI/CD pipelines).
 </li>
 <li>
 Experience with
 
 cloud AI environments
 
 (AWS SageMaker, Azure ML, Google Vertex AI).
 </li>
 <li>
 Familiarity with
 
 data platforms
 
 (Snowflake, Databricks, Power BI, BigQuery).
 </li>
 <li>
 Understanding of
 
 AI ethics, security, and compliance frameworks
 
 .
 </li>
 </ul>
 
 
</div>

AI Engineer / Data Scientist

Splash Software

<div>About the Role
We are seeking a highly motivated Data Scientist with extensive experience in Online Gaming Industry to join our team and drive data-driven decision-making through advanced analytics and machine learning models. The ideal candidate will have a strong technical background, a passion for uncovering insights from complex datasets, and the ability to collaborate with cross-functional teams to solve business challenges.
Key Responsibilities
<ul><li>Design and implement machine learning models to predict trends, detect anomalies, and uncover actionable insights.
</li><li>Analyze structured and unstructured datasets to identify patterns and opportunities for optimization.
</li><li>Develop predictive models and algorithms for key business use cases, such as risk management, forecasting, and segmentation.
 </li><li>Collaborate with data engineers and analysts to ensure data readiness for analysis and model deployment.
 </li><li>Use statistical techniques to validate hypotheses, assess model performance, and improve decision-making processes.
 </li><li>Create and present data-driven insights and recommendations to stakeholders in a clear and compelling manner.
 </li><li>Deploy, monitor, and refine models in production environments to ensure scalability and reliability.
 </li><li>Stay updated on the latest advancements in data science and machine learning, incorporating best practices into projects.
</li></ul>Qualifications
<ul><li>Masters degree in Mathematics or Statistics.
</li><li>Proven experience as a Senior Data Scientist, with expertise in building and deploying machine learning models.
</li><li>Proficiency in Python or R, with experience in data manipulation libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
 </li><li>Strong knowledge of statistical methods, data modeling, and hypothesis testing.
</li><li>Experience working with large-scale data in environments such as Elasticsearch or SQL databases.
</li><li>Familiarity with data visualization tools (e.g., Kibana, Tableau, or Matplotlib) for presenting insights.
 </li><li>Excellent problem-solving and analytical skills with attention to detail.
</li><li> Strong communication skills, with the ability to translate complex data findings into actionable insights for non-technical stakeholders.
</li><li>Experience in the Online Gaming Industry is a Must.
</li></ul>Preferred Skills
<ul><li>Hands-on experience with anomaly detection and forecasting models.
</li><li>Knowledge of big data tools and frameworks (e.g., Hadoop, Spark).
</li><li> Familiarity with MLOps practices and tools for deploying and managing machine learning models in production.
 </li><li>Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for data science workflows.
 </li><li>Understanding of Elasticsearchs machine learning capabilities is a plus.</li></ul></div>

Data Scientist- Online Gaming Experience

BITECH

Proficiency in Python, TensorFlow, PyTorch, and Hugging Face. Working with APIs for OpenAI, Anthropic, Cohere, and Stability AI prompt engineering, fine-tuning LLMs, and RAG techniques Knowledge of vector databases -FAISS, Pinecone, ChromaDB Required Candidate profile Bachelor's or Master s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3+ years of experience in AI, machine learning, or NLP <div>Role: Data Scientist</div><div>Industry Type: IT Services &amp; Consulting</div><div>Department: Data Science &amp; Analytics</div><div>Employment Type: Full Time, Temporary/Contractual</div><div>Role Category: Data Science &amp; Machine Learning</div><div>Education</div><div>UG: B.Tech/B.E. in Artificial Intelligence, Artificial Intelligence And Data Science, Robotics And Automation, Artificial Intelligence And Machine Learning</div>

AI Specialist

steadfast group

We are seeking an experienced and innovative AI Engineer to design, build, and deploy AI-driven solutions that enhance business operations and customer experience. The ideal candidate will have expertise in machine learning, natural language processing, and automation systems, with hands-on experience in developing and integrating AI models into production environments.Key ResponsibilitiesDesign, develop, and deploy AI/ML models and algorithms for business applications.Build and maintain data pipelines for model training and validation.Collaborate with software engineers, data scientists, and business teams to integrate AI capabilities into products and systems.Apply deep learning, NLP, and computer vision techniques to solve real-world problems.Optimize models for scalability, performance, and efficiency.Analyze datasets to identify trends, anomalies, and predictive opportunities.Stay updated with emerging AI technologies, frameworks, and best practices.Prepare technical documentation and participate in project planning and progress reporting.Ensure compliance with data security, governance, and ethical AI standards.Desired ProfileBachelor&rsquo;s or Master&rsquo;s degree in Computer Science, AI, Data Science, or a related field.3&ndash;6 years of experience in AI/ML model development, preferably within the UAE or GCC region.Strong programming skills in Python and libraries such as TensorFlow, PyTorch, Keras, Scikit-learn, and OpenCV.Experience with cloud-based AI environments (AWS SageMaker, Google Vertex AI, Azure ML).Solid understanding of data preprocessing, model evaluation, and deployment.Familiarity with MLOps pipelines and version control tools (Git, Docker).Excellent problem-solving, analytical, and teamwork skills.Salary AED20000 to AED30000Job Type: Full-timePay: AED20,000.00 - AED30,000.00 per month

AI Engineer

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