sales engineer

civil engineer

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field service engineer

ai engineer

ml engineer

Master Works

<div>
 This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, develop, train, and optimize machine learning models for real applications or use cases.
 </li>
 <li>
 Translate business and product requirements into scalable ML/AI solutions.
 </li>
 <li>
 Implement feature engineering, model selection, tuning, and evaluation techniques.
 </li>
 <li>
 Develop , and deploy ML models into production environments with high availability and performance.
 </li>
 <li>
 Build and maintain ML pipelines (training, validation, deployment, monitoring).
 </li>
 <li>
 Monitor model performance, data drift, and model decay; retrain models as needed.
 </li>
 <li>
 Ensure models meet reliability, scalability, and security standards.
 </li>
 <li>
 Work closely with Data Scientists, Product Managers, and Software Engineers.
 </li>
 <li>
 Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.
 </li>
 <li>
 Participate in design and code reviews, ensuring engineering best practices.
 </li>
 <li>
 Optimize models for latency, throughput, and cost.
 </li>
 <li>
 Implement experimentation frameworks (A/B testing, offline evaluation).
 </li>
 <li>
 Apply responsible AI principles, including fairness, explainability, and governance where required
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 3-7+ years of hands-on experience in Machine Learning or applied AI roles.
 </li>
 <li>
 Strong programming skills in Python (and/or Java, Scala).
 </li>
 <li>
 Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
 </li>
 <li>
 Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn.
 </li>
 <li>
 Experience deploying models using Docker, Kubernetes, or cloud ML services.
 </li>
 <li>
 Strong knowledge of data structures, algorithms, and software engineering principles.
 </li>
 <li>
 Experience working in agile, cross-functional teams
 </li>
 <li>
 Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
 </li>
 <li>
 Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
 </li>
 <li>
 Experience with big data technologies (Spark, Kafka, Databricks).
 </li>
 <li>
 Background in NLP, Computer Vision, or Generative AI.
 </li>
 <li>
 Strong problem-solving and analytical thinking
 </li>
 <li>
 Production-first mindset
 </li>
 <li>
 Data-driven decision making
 </li>
 <li>
 High Collaboration and communication skills
 </li>
 </ul>
</div>

ML Engineer

MASTER-WORKS

<div>This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.
Key Responsibilities:
<ul><li>Design, develop, train, and optimize machine learning models for real applications or use cases.
</li><li>Translate business and product requirements into scalable ML/AI solutions.
</li><li>Implement feature engineering, model selection, tuning, and evaluation techniques.
</li><li>Develop , and deploy ML models into production environments with high availability and performance.
</li><li>Build and maintain ML pipelines (training, validation, deployment, monitoring).
</li><li>Monitor model performance, data drift, and model decay; retrain models as needed.
</li><li>Ensure models meet reliability, scalability, and security standards.
</li><li>Work closely with Data Scientists, Product Managers, and Software Engineers.
</li><li>Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.
</li><li>Participate in design and code reviews, ensuring engineering best practices.
</li><li>Optimize models for latency, throughput, and cost.
</li><li>Implement experimentation frameworks (A/B testing, offline evaluation).
</li><li>Apply responsible AI principles, including fairness, explainability, and governance where required.</li></ul> 
Requirements 
<ul><li>
3&ndash;7+ years of hands-on experience in Machine Learning or applied AI roles.
</li><li>Strong programming skills in Python (and/or Java, Scala).
</li><li>Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
</li><li>Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn.
</li><li>Experience deploying models using Docker, Kubernetes, or cloud ML services.
</li><li>Strong knowledge of data structures, algorithms, and software engineering principles.
</li><li>Experience working in agile, cross-functional teams.</li><li>
Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
</li><li>Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
</li><li>Experience with big data technologies (Spark, Kafka, Databricks).
</li><li>Background in NLP, Computer Vision, or Generative AI.
</li><li>Strong problem-solving and analytical thinking
</li><li>Production-first mindset
</li><li>Data-driven decision making
</li><li>High Collaboration and communication skills</li></ul></div>

TAWANTECH

<div>Job Summary: 
 
We are looking for a Machine Learning Engineer with 4+ years of experience in building, deploying, and optimizing ML models in software environments. The ideal candidate has strong Python skills and hands-on experience delivering production-ready ML solutions.
Key Responsibilities:<ul><li>
Develop, train, and deploy machine learning models.
</li><li>Build scalable data pipelines and integrate ML into applications.
</li><li>Perform data preprocessing, feature engineering, and model evaluation.
</li><li>Monitor model performance and implement improvements.
</li><li>Collaborate with engineering and product teams in agile environments.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s in Computer Science, AI, or related field.
</li><li>4+ years of ML experience in software/product companies.
</li><li>Strong Python skills and experience with TensorFlow, PyTorch, or Scikit-learn.
</li><li>Experience deploying models in production (cloud preferred: AWS/Azure/GCP).
</li><li>Good understanding of statistics, algorithms, and MLOps practices.</li></ul></div>

Machine Learner Engineer

<div>
 
 Job Summary:
 
 
 
 We are looking for a Machine Learning Engineer with 4+ years of experience in building, deploying, and optimizing ML models in software environments. The ideal candidate has strong Python skills and hands-on experience delivering production-ready ML solutions.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Develop, train, and deploy machine learning models.
 </li>
 <li>
 Build scalable data pipelines and integrate ML into applications.
 </li>
 <li>
 Perform data preprocessing, feature engineering, and model evaluation.
 </li>
 <li>
 Monitor model performance and implement improvements.
 </li>
 <li>
 Collaborate with engineering and product teams in agile environments
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's or Master's in Computer Science, AI, or related field.
 </li>
 <li>
 4+ years of ML experience in software/product companies.
 </li>
 <li>
 Strong Python skills and experience with TensorFlow, PyTorch, or Scikit-learn.
 </li>
 <li>
 Experience deploying models in production (cloud preferred: AWS/Azure/GCP).
 </li>
 <li>
 Good understanding of statistics, algorithms, and MLOps practices
 </li>
 </ul>
</div>

<div>
 About the Role:
 
 
 Master works is looking for an experienced
 
 LLM Engineer
 
 to join our team working on next-generation AI-driven analytics solutions. The ideal candidate will design and implement natural language search, semantic search solutions, and generative AI features for our web applications. You will work hands-on with advanced language models, vector databases, RAG pipelines, and build intelligent workflows to enable actionable insights from both structured and unstructured data.
 
 
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Develop and maintain natural language search capabilities and semantic search solutions using vector databases.
 </li>
 <li>
 Implement NL-to-SQL pipelines and other intelligent query generation features for analytics platforms.
 </li>
 <li>
 Build and optimize Generative AI features (summarization, recommendations, insights) for analytics applications.
 </li>
 <li>
 Design and implement Agents and Workflows for complex tasks across datasets.
 </li>
 <li>
 Develop RAG (Retrieval-Augmented Generation) pipelines for knowledge retrieval and query resolution.
 </li>
 <li>
 Create embeddings for structured and unstructured data and leverage them for semantic understanding and search.
 </li>
 <li>
 Process and transform structured (tables, CSV, SQL) and unstructured data (text, documents, logs) as input/output for AI models.
 </li>
 <li>
 Collaborate with data engineers, analysts, and product teams to integrate AI features seamlessly into the platform.
 </li>
 <li>
 Evaluate, benchmark, and optimize LLM performance for real-world analytics use cases.
 
 
 </li>
 </ul>
 
 Required Qualifications &amp; Skills:
 
 
 
 <ul>
 <li>
 Bachelor's or master's degree in computer science, AI/ML, Data Science, or related field.
 </li>
 <li>
 Hands-on experience with LLMs (OpenAI, Anthropic, Cohere, or similar).
 </li>
 <li>
 Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
 </li>
 <li>
 Strong understanding of embeddings, semantic search, and their practical applications.
 </li>
 <li>
 Expertise in RAG pipelines, Agents, and Workflow orchestration.
 </li>
 <li>
 Proficiency in Python and relevant AI/ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow).
 </li>
 <li>
 Familiarity with NL-to-SQL systems and natural language query processing.
 </li>
 <li>
 Experience working with structured and unstructured data sources.
 </li>
 <li>
 Knowledge of data pipelines, preprocessing, and storage formats for analytics.
 </li>
 <li>
 Ability to design scalable, production-ready AI solutions integrated with web applications.
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 Experience working with AI based chatbots, Natural language search, NL to SQL.
 </li>
 <li>
 Knowledge of prompt engineering and fine-tuning LLMs.
 </li>
 <li>
 Familiarity with data privacy, security, and compliance considerations in AI pipelines.
 
 
 </li>
 </ul>
 
 Soft Skills:
 
 
 
 <ul>
 <li>
 Strong problem-solving and analytical skills.
 </li>
 <li>
 Excellent communication skills to work with cross-functional teams.
 </li>
 <li>
 Passion for AI and staying up to date with the latest developments in LLMs and generative AI.
 </li>
 </ul>
</div>

LLM engineer

MOZN

<div>
 
 About Mozn
 
 
 
 MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
 
 
 We&rsquo;re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
 
 
 If you&rsquo;re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
 
 
 
 About The Role
 
 
 
 We are searching for a strategic and inquisitive Data Scientist. As a member of Mozn's Data Science team, you will work with cross-disciplinary teams to identify the problems to be solved, specify the problems in mathematical and statistical terms, scope out the project/product in collaboration with your team and external stakeholders, and then go about answering the identified questions. You find insights that spur teams and stakeholders to improve their business/product and drive value for internal and external stakeholders.
 
 
 
 
 What you&rsquo;ll d
 
 
 
 
 o
 
 
 
 
 <ul>
 <li>
 Work with cross-functional teammates from engineering, products, business, and marketing to deliver data-powered solutions.
 </li>
 <li>
 Communicate highly technical results and methods clearly to a wide variety of external clients.
 </li>
 <li>
 Analyze and extract insights from multiple and complex datasets through regression analysis, hypothesis testing, and other machine learning techniques.
 </li>
 <li>
 Develop and apply new machine learning techniques to ensure modern yet optimal approaches are applied to Mozn's solutions.
 </li>
 <li>
 Develop data pipelines and ingestion engines for Natural Language Understanding and/or Risk Management; as well as contribute to current engines at Mozn.
 </li>
 <li>
 Engage with stakeholders to identify and define the scope of challenges and propose data-powered solutions.
 </li>
 <li>
 Plan and execute solutions' development from data gathering to intelligent decision making.
 </li>
 <li>
 Staying informed with new frameworks and technological advances to increase Mozn's efficiency and productivity.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 B.S. or M.S. in Computer Science, Statistics, Mathematics or similar quantitative fields.
 </li>
 <li>
 3-5 years of Relevant experience as a data scientist, or similar fields that require developing ML/AI models. Over 2 years for B.S. degree and over 1 year for M.S.
 </li>
 <li>
 Programming experience over two years in object oriented programming, including data manipulation using Python or other languages.
 </li>
 <li>
 Good understanding of statistics and probability, such as Bayesian methods and conditional probability.
 </li>
 <li>
 Applied experience in machine learning, such as conducting model experiments.
 </li>
 <li>
 Experience in version control systems, such as Git, GitHub.
 </li>
 <li>
 Programming experience in SQL or NoSQL is preferred.
 </li>
 <li>
 Familiarity with big data technologies, such as Spark.
 </li>
 <li>
 Experience in deep learning frameworks, such as PyTorch.
 </li>
 <li>
 Expertise in Natural Language Understanding and/or Risk Management applications.
 </li>
 <li>
 Familiarity with containerization frameworks, such as Docker.
 </li>
 <li>
 Research experience in optimization and natural language processing (NLP).
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
 </li>
 <li>
 You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
 </li>
 <li>
 The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
 </li>
 <li>
 You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
 </li>
 <li>
 We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.
 </li>
 </ul>
</div>

Data Scientist

Devoteam

<div>
 
 Tech for People Unlocks the Future
 
 
 
 At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us.
 
 
 With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.
 
 
 
 Devoteam Culture &amp; Values:
 
 
 
 True innovation is born from a powerful culture, fused with meaningful values.
 
 
 
 Culture:
 
 
 
 
 Fair and courageous
 
 
 
 Everyone is treated fairly &ndash; this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.
 
 
 
 Ambition and results
 
 
 
 Ambition is nurtured at every step &ndash; this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.
 
 
 
 Learning and innovating
 
 
 
 Curiosity and learning are at our core &ndash; this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.
 
 
 
 Caring and sharing
 
 
 
 A caring attitude is infused into our culture &ndash; this encourages sharing. We believe in the power of teams, we promote support and collaboration.
 
 
 At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers,
 
 
 
 Values:
 
 
 
 <ul>
 <li>
 Respect
 </li>
 <li>
 Frankness
 </li>
 <li>
 Passion
 
 
 
 </li>
 </ul>
 Knowing that success is the result of collaboration. Alone, we go faster, but together, we go further.
 
 
 To know more about us, please visit: www.devoteam.com
 
 
 
 Job Description
 
 
 
 As a Senior Data Scientist\Machine Learning Engineer at Devoteam, you will be responsible for developing, implementing, and optimizing advanced data-driven algorithms, including classification, regression, recommender systems, and user segmentation models. You will collaborate with cross-functional teams to identify opportunities for improvement and deliver impactful insights that drive business success
 
 
 Key responsibilities :
 
 
 <ul>
 <li>
 Identifying relevant data sources for business needs.
 </li>
 <li>
 Processing, cleansing, and Organising data into usable formats.
 </li>
 <li>
 Conduct in-depth research and analysis on large datasets to uncover hidden patterns, correlations, and trends
 </li>
 <li>
 Apply data mining techniques such as association rule discovery, classification, and clustering
 </li>
 <li>
 Conduct thorough EDA to understand underlying patterns, correlations, and anomalies in complex datasets
 </li>
 <li>
 Transform and preprocess raw data to create meaningful features that can improve model performance.
 </li>
 <li>
 Develop, evaluate, and deploy predictive machine learning models to drive actionable insights.
 </li>
 <li>
 Communicate complex data findings in a clear and concise manner to non-technical stakeholders
 </li>
 <li>
 Stay up-to-date with the latest advancements in data science, machine learning, and industry best practices, continuously seeking opportunities to improve methodologies and processes.
 </li>
 <li>
 Advanced Technical Skills: Mastery of programming languages like Python or R, expertise in data manipulation, machine learning algorithms, and statistical analysis.
 </li>
 <li>
 Data Manipulation:** Proficiency in working with large datasets, data cleaning, preprocessing, and transforming data into usable formats.
 </li>
 <li>
 Machine Learning Expertise:** Experience in selecting and implementing appropriate machine learning algorithms, model evaluation, hyperparameter tuning, and dealing with bias and fairness issues.
 </li>
 <li>
 Build conversational AI applications.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Engineering, IT or equivalent
 </li>
 <li>
 + 7 year experience within the data science field.
 </li>
 <li>
 Has a strong knowledge and proven experience in following areas: SQL, statistics , machine learning and programming
 </li>
 <li>
 Strong expertise in various supervised and unsupervised machine learning algorithms such as Time Series Forecasting ,regression ,Clustering,Classification and deep learning methods
 </li>
 <li>
 Experience working with Agile methodologies
 </li>
 <li>
 Ability to communicate with both technical and non-technical audiences
 </li>
 <li>
 Excellent English and Arabic communication skills (written &amp; spoken)
 </li>
 <li>
 Analytical mindset and Problem-solving skills
 </li>
 <li>
 Alteryx or Dataiku experience is a must
 </li>
 <li>
 MLOps experience is a plus
 </li>
 <li>
 Practical Knowledge of big data systems is a plus
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 BU: Data Intelligence
 
 
 Senio Level
</div>

Senior Data Scientist

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