data engineer

mechanical engineer

senior software engineer

ai engineer

ai/ml engineer

machine learning engineer

Envision Employment Solutions

Envision Employment Solutions is currently looking for a Machine Learning Engineer for one of our partners, a global leader in consulting, digital transformation, technology, and engineering services.
 
Responsibilities: 
<ul>
<li>Machine Learning & AI Solutions</li>
<li>Deploy advanced machine learning models and AI-driven solutions across cloud environments.</li>
<li>Lead the end-to-end lifecycle of ML models, from data ingestion and feature engineering to model training, evaluation, and deployment.</li>
<li>Monitor model performance and implement retraining strategies to ensure long-term accuracy and relevance.</li>
<li>Cloud & Data Engineering</li>
<li>Architect and optimize scalable data pipelines and cloud-based infrastructures (Azure, AWS, or GCP) to support ML workloads.</li>
<li>Collaborate with data engineers to ensure robust data preprocessing, transformation, and storage strategies.</li>
<li>MLOps & Automation</li>
<li>Develop and maintain CI/CD pipelines tailored for ML workflows, including automated testing, model versioning, and deployment.</li>
<li>Integrate monitoring and alerting systems to track model drift, data quality, and system performance.</li>
<li>Collaboration & Innovation</li>
<li>Work closely with cross-functional teams including data scientists, product managers, and business stakeholders to translate business needs into technical solutions.</li>
<li>Mentor junior engineers and contribute to knowledge sharing and best practices across the team.</li>
</ul>
Requirements: 
<ul>
<li>Technical Skills</li>
<li>Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).</li>
<li>Strong command of SQL and experience with large-scale data processing tools (e.g., Spark, Pandas).</li>
<li>Deep understanding of cloud platforms (Azure, AWS, GCP) and their ML services.</li>
<li>Skilled in MLOps practices, including CI/CD, containerization (Docker), and orchestration (Kubernetes).</li>
<li>Familiarity with Git and collaborative development workflows.</li>
<li>Experience</li>
<li>6+ years of experience working with complex datasets and solving real-world business problems using AI</li>
<li>Proven track record of deploying and maintaining ML models in production environments.</li>
<li>Communication Skills</li>
<li>Excellent written and verbal communication skills to collaborate effectively with cross-functional teams.</li>
<li>Fluent in Qatari Arabic & English, both spoken and written.</li>
<li>Additional Skills</li>
<li>Strong problem-solving abilities and attention to detail.</li>
<li>Ability to work collaboratively in a team environment.</li>
<li>Self-motivated with a continuous learning mindset.</li>
<li>Team management.</li>
</ul>
Benefits: 
<ul>
<li>Competitive Salary based on experience</li>
<li>Social and medical insurance</li>
<li>Learning, development and career progression</li>
</ul>

Machine Learning Engineer

Specright

<div>Job Title: Machine Learning Engineer
Job Summary
Specright is seeking a highly motivated and talented Machine Learning Engineer to join the Shared Services team. As a Machine Learning Engineer, you will have the opportunity to design, develop, and maintain scalable cloud-based ML pipelines, evaluate and provide recommendations based on best practices, and collaborate with other technical team members.
Specright offers cloud-based software (SaaS) for specification data management to Enterprise and Mid-Market level companies with complex needs. Whether it's packaging, formulas, or products, Specright helps companies reduce costs and empower efficiencies by sharing, analyzing and auditing specifications.
Responsibilities and Duties<ul><li>
Design, implement, and maintain ML pipelines to support machine learning model validation and deployment in a cloud-based environment</li><li>
Optimize and enhance existing machine learning systems and data pipelines for improved performance and scalability</li><li>
Collaborate effectively with technical team members to define system requirements and deployment strategies</li><li>
Provide support and troubleshooting to engineers and customers for new and existing deployments</li><li>
Provide support and guidance to other AI/ML team members</li></ul>
Qualifications<ul><li>
Highly experienced in designing and managing scalable ML pipelines in a cloud-based environment such as AWS</li><li>
Experience with scripting languages such as Python and Bash</li><li>
Experience with CI/CD platforms such as Jenkins</li><li>
Experience with NLP (e.g. classification, NER, etc.), LLMs, or Computer Vision (e.g. recognition, detection, segmentation)</li><li>
Ability to code, test, and debug service issues at multiple levels within a stack using multiple languages and platforms</li></ul>
Preferred Qualifications<ul><li>
B.S. or M.S. in Computer Science, Electrical Engineering, or related fields</li><li>
Deep understanding of cross-functional AWS services and organizational cloud management</li></ul>
About Specright
Specright is the first purpose-built, patented platform for Specification Management. Whether it's
packaging, raw materials, formulas, products, or machines, Specright helps companies digitize, map, and take action across their supply chain to reduce costs, increase profitability, and drive sustainability. Specright serves customers across industries, including packaging, food and beverage, consumer packaged goods, pharmaceutical, retail, industrials, and more. Recognized as a leader in Specification Management, Specright was named to the Deloitte Fast Technology 500 list in 2024, one of Fast Company's Most Innovative Companies for 2023, had three executives honored as SupplyDemand Chain Executive Pros to Know in 2023 and won Food Logistics' 2022 Top SoftwareTechnology Provider award. For more information, visit: www.specright.com.
Location
Cairo, Egypt.
Culture
We are an energetic company with an entrepreneurial, informal, versatile, intelligent, and fast-paced culture. We promote an open and relatively flat organization with an emphasis on collaboration, sharing ideas and information. It's more important to innovate, then worry about making mistakes.
Perks<ul><li>
Competitive salaries</li><li>
Flexible work hours</li><li>
Full benefits package that includes Medical, Vision, and Dental</li></ul></div>

Synapse Analytics

<div>As a Senior Machine Learning Engineer at Synapse Analytics, you'll be a machine learning leader, driving the development of complex and critical model-driven product areas. You'll take ownership of major features and initiatives, contributing significantly to the product strategy and ensuring the high quality, scalability, and market fit of our applications. You'll also play a crucial role in mentoring and guiding less experienced engineers, fostering a culture of excellence and continuous improvement.<h3 class="jobSectionHeader">
Responsibilities</h3><ul><li>
Lead the product discovery, definition, and delivery of major machine learning initiatives and complex features.</li><li>
Design and advocate for significant model architecture decisions, ensuring alignment with the overall business strategy and user needs.</li><li>
Set and enforce high standards for machine learning practices, best practices, and principles across the team, leading by example.</li><li>
Mentor and coach Machine Learning Engineer I and II colleagues, providing deep technical guidance, fostering their growth, and leading strategic discussions.</li><li>
Solve highly complex, ambiguous, and strategic modeling challenges that have a broad impact on the product or the organization.</li><li>
Collaborate extensively with senior leadership, engineering, design, and other stakeholders to define requirements, evaluate feasibility, and deliver robust, integrated solutions.</li><li>
Identify and address critical market opportunities, user pain points, and competitive threats through machine learning.</li><li>
Proactively identify, prioritize, and lead efforts to address model debt and process inefficiencies.</li><li>
Research, evaluate, and propose new ML strategies and technologies to improve the product offering and development processes.</li><li>
Act as a primary point of contact for complex model-related issues, leading diagnosis and resolution.</li></ul><ul><li>
BS/BA, MS, or PhD equivalent in Computer Science, Engineering, or a related field.</li><li>
4+ years of experience in a machine learning or applied science role.</li><li>
Deep expertise in Python and extensive experience with ML frameworks like PyTorch, Tensorflow, and scikit-learn.</li><li>
Expert knowledge and experience in defining model vision, strategy, and roadmaps.</li><li>
Excellent experience in designing, building, and managing large-scale, production-grade machine learning systems.</li><li>
Expert understanding of computer vision, NLP, or another core ML domain relevant to our products.</li><li>
Excellent troubleshooting skills, including solving complex user problems and navigating business ambiguities.</li><li>
Expert understanding of the end-to-end product development lifecycle.</li><li>
Deep knowledge of MLOps, system architecture, and the technical aspects of software development.</li><li>
Strong experience in mentoring and developing junior team members.</li><li>
Excellent communication skills and experience in stakeholder management and influencing without authority.</li></ul></div>

Senior Machine Learning Engineer (Computer Vision)

<div>As a Machine Learning Engineer II at Synapse Analytics, you will be a key individual contributor responsible for guiding the development of robust, scalable, and high-value models for our core products. You'll move beyond assisting with model implementation to taking ownership of more complex ML components and contributing significantly to the roadmap and strategy. You will also begin to mentor junior team members.<h3 class="jobSectionHeader">
Responsibilities</h3><ul><li>
Design, implement, and manage the end-to-end lifecycle for significant ML models and features.</li><li>
Ensure the value and feasibility of model requirements by collaborating closely with design and engineering teams.</li><li>
Optimize model pipelines for maximum value, speed, and alignment with strategic goals.</li><li>
Explore and visualize data to identify distributions that could affect performance, and define robust validation strategies.</li><li>
Analyze model errors and design effective strategies to overcome them.</li><li>
Collaborate closely with stakeholders, designers, and the development team to define requirements and deliver integrated solutions.</li><li>
Clearly and regularly communicate model decisions, progress, and challenges with management and cross-functional teams.</li><li>
Lead model refinement sessions for peers and junior engineers, providing in-depth constructive feedback.</li><li>
Research and stay up-to-date with the latest market trends and user needs, actively proposing and evaluating new opportunities for the product.</li></ul><ul><li>
Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent work experience.</li><li>
2-4 years of experience in a machine learning-focused role.</li><li>
Excellent knowledge and extensive experience in Python and machine learning frameworks such as PyTorch, Tensorflow, and scikit-learn.</li><li>
Strong understanding of and experience with computer vision techniques, including image/video processing, object detection, and recognition.</li><li>
Excellent knowledge and experience in data preprocessing, feature extraction, data augmentation, and dimensionality reduction techniques.</li><li>
Expertise in visualizing and manipulating big datasets.</li><li>
Strong experience with UNIX/Linux environments, Git, and Docker.</li><li>
Excellent troubleshooting skills for resolving requirement ambiguities and model performance conflicts.</li><li>
Excellent understanding of the product development lifecycle, from discovery to deployment.</li><li>
Experience with Kubernetes is a strong plus.</li></ul></div>

Machine Learning Engineer II (Computer Vision)

Appgain

APPGAIN is seeking an innovative and experienced AI Engineer to join our dynamic team. As an AI Engineer, you will be instrumental in designing, developing, and deploying cutting-edge artificial intelligence and machine learning solutions that address complex business challenges. You will work at the intersection of data science, software engineering, and operations to bring AI models from research to production.Responsibilities:<ul><li>Design, develop, and implement scalable AI models and algorithms using machine learning and deep learning techniques.</li><li>Build and manage robust AI development and production infrastructure, including data pipelines and MLOps workflows.</li><li>Collaborate with data scientists, product managers, and other stakeholders to translate business requirements into AI-driven solutions.</li><li>Integrate AI models into existing software systems and applications, ensuring seamless functionality and performance.</li><li>Conduct statistical analysis and interpret results to optimize AI models and guide decision-making.</li><li>Perform model testing, validation, and debugging to ensure accuracy, reliability, and efficiency.</li><li>Monitor and maintain deployed AI systems, identifying and resolving issues, and continuously optimizing performance.</li><li>Stay up-to-date with the latest advancements in AI research, technologies, and industry best practices.</li><li>Contribute to the adoption of AI best practices across teams and promote a data-driven culture.</li><li>Document machine learning processes, models, and solutions thoroughly.</li></ul>Qualifications:<ul><li>Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.</li><li>Proven experience as an AI Engineer, Machine Learning Engineer, or a similar role, with a strong portfolio of deployed AI solutions.</li><li>Proficiency in programming languages commonly used in AI, such as Python (with libraries like TensorFlow, PyTorch, Keras) or Java.</li><li>Solid understanding of machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning neural networks.</li><li>Experience with big data technologies (e.g., Apache Spark, Hadoop, MongoDB) and data processing techniques.</li><li>Strong knowledge of SQL and experience with database modeling and management.</li><li>Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI/ML services.</li><li>Excellent problem-solving, analytical, and critical thinking skills.</li><li>Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.</li><li>Ability to work effectively in an agile, fast-paced, and collaborative environment.</li><li>Experience with Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.</li><li>Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes).</li><li>Experience with prompt engineering for Large Language Models (LLMs).</li><li>Familiarity with software design patterns and principles.</li><li>Contributions to open-source AI projects or relevant publications.</li></ul>Job Type: full time on siteJob Type: Full-timeEducation:<ul><li>Bachelor's (Preferred)</li></ul>Experience:<ul><li>AI Engineer: 3 years (Preferred)</li><li>machine learning algorithms : 3 years (Preferred)</li><li>big data technologies : 3 years (Preferred)</li></ul>

AI Engineer

DXC Technology

<div>
 
 
 Job Description
 
 
 
 
 Role Overview:
 
 
 
 We are seeking a highly skilled and collaborative Data Scientist to join the delivery team for a strategic Data &amp; AI implementation project. The ideal candidate will support the platform&rsquo;s advanced analytics use cases, including data exploration, statistical modeling, feature engineering, ML model development, and GenAI use case enablement. You will collaborate with data engineers, architects, BI developers, and business stakeholders to deliver actionable insights and intelligent solutions.
 
 
 
 Key Responsibilities
 
 
 
 
 🔹 Data Exploration &amp; Feature Engineering:
 
 
 <ul>
 <li>
 Explore, profile, and analyze structured, semi-structured, and unstructured data across more than 11 enterprise source systems (e.g., SAP, Oracle Fusion, JIRA, Primavera, etc.)
 </li>
 <li>
 Perform data cleansing, feature selection, and transformation activities across Bronze and Silver layers of the Lambda Data Lakehouse architecture
 </li>
 </ul>
 
 
 🔹 Advanced Analytics &amp; ML
 
 
 <ul>
 <li>
 Develop, train, and optimize supervised and unsupervised machine learning models to support use cases such as customer churn prediction, financial chatbot insights, and operational efficiency improvements
 </li>
 <li>
 Support integration and deployment of ML models into the data platform using tools like Google Cloud AI Platform, Python, Snowflake, and Power BI
 </li>
 </ul>
 
 
 🔹 GenAI Enablement
 
 
 <ul>
 <li>
 Collaborate on use cases involving Generative AI and Large Language Models (LLMs) using structured and unstructured datasets
 </li>
 <li>
 Work with data architects to ensure the Lakehouse architecture supports these models effectively
 </li>
 </ul>
 
 
 🔹 Collaboration &amp; Business Engagement
 
 
 <ul>
 <li>
 Participate in workshops and requirement-gathering sessions with customer&rsquo;s business and technical teams
 </li>
 <li>
 Translate business questions into data science problems, and present findings in actionable, business-friendly formats (dashboards, reports, presentations)
 </li>
 </ul>
 
 
 🔹 Quality, Testing &amp; Governance
 
 
 <ul>
 <li>
 Document assumptions, modeling approaches, and validations
 </li>
 <li>
 Participate in unit testing, QA, and UAT activities related to predictive analytics and AI models
 </li>
 <li>
 Ensure compliance with NDMO, PDPL, and customer&rsquo;s internal data governance policies
 </li>
 </ul>
 
 
 Required Skills And Experience
 
 
 <ul>
 <li>
 Strong experience in data science or machine learning roles on large-scale enterprise data projects
 </li>
 <li>
 Strong hands-on experience in:
 </li>
 <li>
 Python, Pandas, Scikit-learn, TensorFlow or PyTorch
 </li>
 <li>
 SQL (Snowflake or Google BigQuery preferred)
 </li>
 <li>
 Data wrangling and feature engineering
 </li>
 <li>
 Experience with ML lifecycle and MLOps tools on Google Cloud Platform (GCP)
 </li>
 <li>
 Familiarity with data versioning, CI/CD for ML, and monitoring ML pipelines
 </li>
 <li>
 Knowledge of APIs, data integration methods, and working with virtualized layers (e.g., Denodo)
 </li>
 <li>
 Exposure to BI visualization tools like Power BI
 </li>
 <li>
 Understanding of data privacy, security, and model fairness in regulated environments
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Google Cloud Certified Data Engineer / Machine Learning Engineer (preferred but not mandatory)
 </li>
 <li>
 Experience working in real estate or public sector is a plus
 </li>
 <li>
 Understanding of data cataloging, metadata, and lineage concepts using Informatica Cloud
 </li>
 </ul>
 
 
 Soft Skills
 
 
 <ul>
 <li>
 Strong analytical mindset and problem-solving skills
 </li>
 <li>
 Excellent communication and stakeholder engagement abilities
 </li>
 <li>
 Ability to work under pressure and deliver in fast-paced, multi-vendor environments
 </li>
 </ul>
 
 At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We&rsquo;re committed to fostering an inclusive environment where everyone can thrive.
 
 
 Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here
 
 .
 
 
</div>

Data Scientist

Explore 1042+ Machine learning engineer in Egypt this November. Find roles across top companies and apply now to boost your career.

1042 machine learning engineer jobs IN Egypt

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Senior Machine Learning Engineer (Computer Vision)

Machine Learning Engineer II (Computer Vision)

AI Engineer

Data Scientist