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machine learning engineer

Smart Eye

<div>
 Smart Eye is the leading provider of Human Insight AI, technology that understands, supports and predicts human behavior in complex environments. The company is on a mission to bridge the gap between humans and machines for a safe and sustainable future. Supported by Affectiva and iMotions &ndash; companies it acquired in 2021 &ndash; Smart Eye&rsquo;s multimodal software and hardware solutions provide unparalleled insight into human behavior.
 
 
 In automotive, Smart Eye&rsquo;s driver monitoring systems and interior sensing solutions improve road safety and the mobility experience. The company&rsquo;s eye tracking technology and iMotions biosensor software platform are also used in behavioral research to enable advanced research in academic and commercial sectors. In media analytics, Affectiva&rsquo;s Emotion AI provides the world&rsquo;s largest brands and market researchers with a deeper understanding of how consumers engage with content, products, and services.
 
 
 Founded in 1999, Smart Eye is a global company headquartered in Sweden, with customers including NASA, Nissan, Boeing, Honeywell, Volvo, GM, BMW, Polestar, Geely, Harvard University, 26 percent of the Fortune Global 500 companies, and over 1,300 research organizations around the world.
 
 
 Visit
 
 www.smarteye.ai
 
 for more information.
 
 
 You will be part of one of Smart Eye's algorithm development teams responsible for development in key areas such as head- and eye-tracking, attentiveness and drowsiness, face identification and interior sensing for our Automotive Cabin and Driving Monitoring product. We work in an international environment with colleagues in Gothenburg (SE) and Boston (US).
 
 
 We are building safety features in novel technology that will significantly improve road safety and will transform our transportation experiences. Safety features such as determining people&rsquo;s seating locations in a vehicle, if they are wearing seat belts, and detection of left-behind children, as well as features that enhance comfort, wellness, and entertainment by detecting occupants&rsquo; emotions and gestures.
 
 
 Development activities range from early-stage prototyping to porting and deployment to a wide set of automotive embedded platforms. And you will be responsible for the complete chain of development activities including protocols for data collection, network architecture, training of networks, exploratory data analysis and visualization, but also integration into and validation of the model in the production software.
 
 
 We solve these challenging problems by utilizing state-of-the-art algorithms in the fields of image processing, the latest machine learning techniques, mathematics, and accelerated computing.
 
 
 You will have an active impact on the processes and projects and will work in close cooperation with other talented team members. Your contribution to how we can meet our customers' needs with tomorrow's technology will be of crucial importance.
 
 
 Who are you?
 
 
 <ul>
 <li>
 We welcome all types of personalities and believe in a true mix of people to create a dynamic work environment.
 </li>
 <li>
 You're able to work independently in an environment that changes rapidly.
 </li>
 <li>
 Exhibit a positive, enthusiastic, open, entrepreneurial attitude and a willingness to work closely with customers or other teams within Smart Eye.
 </li>
 <li>
 Possess strong analytical, creative skills with a strong interest in new technologies.
 
 
 </li>
 </ul>
 
 Must-have-skills
 
 
 
 <ul>
 <li>
 Degree in Electrical Engineering, Computer Sciences, or Mathematics with specialization in computer vision or machine learning.
 </li>
 <li>
 Experience using end-to-end development of machine learning based systems (design, planning, evaluation, deployment).
 </li>
 <li>
 3+ years of software development experience.
 </li>
 <li>
 3+ years of work experience in C++ and Python development.
 </li>
 <li>
 Strong communication and team collaboration skills.
 
 
 </li>
 </ul>
 
 Good-to-have-skills
 
 
 
 <ul>
 <li>
 Experience in optimizing Deep Learning model architectures and inference runtimes (ex. Tensorflow, Tensorflow Lite, PyTorch).
 </li>
 <li>
 Experience in one or more fields of image processing or graphics programming.
 </li>
 <li>
 Experience with CI/CD (Continuous Integration and Deployment).
 </li>
 <li>
 Experience in developing software for the Automotive industry.
 </li>
 <li>
 Familiar with Agile methodologies (has worked with Git, Jira and alike).
 </li>
 </ul>
</div>

Machine Learning Engineer

Arrow Electronics

<div>
 
 Position
 
 
 
 Data Scientist / Senior Machine Learning Engineer
 
 
 
 Job Description
 
 
 
 
 Position Overview:
 
 
 
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
 </li>
 <li>
 Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
 </li>
 <li>
 Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
 </li>
 <li>
 Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
 </li>
 <li>
 Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
 </li>
 <li>
 Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
 </li>
 <li>
 Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
 </li>
 <li>
 Strong knowledge of machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in data preprocessing, feature engineering, and model selection.
 </li>
 <li>
 Familiarity with large language models and AI agent design.
 </li>
 <li>
 Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
 </li>
 <li>
 Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience with vectorized databases and unstructured search engines is a plus.
 </li>
 <li>
 A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
 </li>
 <li>
 Publications or contributions to open-source projects are a plus.
 
 
 </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 
 
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Data Scientist / Senior Machine Learning Engineer

Valeo

<div>
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, train, and deploy machine learning models tailored for resource-constrained edge hardware.
 </li>
 <li>
 Apply data science methodologies to perform Exploratory Data Analysis (EDA), statistical modeling, and visualization of complex time-series data from powertrain sensors to inform model architecture.
 </li>
 <li>
 Perform feature engineering to clean, process, and structure raw sensor datasets, ensuring they are optimized and ready to be fed into the models.
 </li>
 <li>
 Conduct hyperparameter tuning to continuously optimize machine learning models for higher accuracy and peak performance.
 </li>
 <li>
 Optimize model inference and runtime predictions to meet strict real-time execution constraints on target edge hardware.
 </li>
 <li>
 Develop real-time application logic using C and C++ while leveraging Python for model training and data preprocessing.
 </li>
 <li>
 Optimize ML models using techniques such as quantization (e.g., float32 to int8), model pruning, and memory optimization.
 </li>
 <li>
 Process, filter (e.g., using Kalman filters), and synchronize noisy data acquired from physical temperature and current sensors.
 </li>
 <li>
 Interface with and customize hardware platforms, including Raspberry Pi capabilities, Linux/Raspbian OS, GPIO, and SPI.
 </li>
 <li>
 Test, benchmark, and validate the performance of ML estimators against real hardware setups or high-fidelity powertrain simulators.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Proven experience in feature engineering, dataset preparation, and data pipeline development.
 </li>
 <li>
 Solid background in applied data science, statistical analysis, anomaly detection, and data visualization for time-series sensor data.
 </li>
 <li>
 Strong knowledge of hyperparameter tuning methodologies to maximize model accuracy and efficiency.
 </li>
 <li>
 Deep understanding of model inference optimization and low-latency runtime prediction behavior.
 </li>
 <li>
 Strong programming skills in C, C++, and Python.
 </li>
 <li>
 Deep understanding of Raspberry Pi hardware, Linux/Raspbian OS customization, and embedded hardware interfaces (GPIO, SPI).
 </li>
 <li>
 Practical experience in model optimization, quantization, and pruning to meet strict hardware constraints.
 </li>
 <li>
 Solid background in signal processing and handling noisy data from physical sensors.
 </li>
 <li>
 Experience validating ML models against real hardware or advanced simulators.
 </li>
 <li>
 Experience in TensorFlow Lite for Microcontrollers &amp; SciKit Learn is a plus
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 3+ years of relevant experience in machine learning, edge computing, or embedded software development.
 </li>
 </ul>
</div>

Software Engineer - Machine Learning (SDV), POWER

<div>
 
 
 About the Role
 
 
 
 
 
 
 We are seeking an experienced AI/ML Developer Level II to join our Innovation &amp; Software Solutions team. In this role, you will be responsible for designing, developing, deploying, and optimizing enterprise-grade conversational AI solutions using the RASA framework, Python, and Google Cloud Platform (GCP). Working closely with cross-functional teams, you will build scalable, production-ready virtual assistants and intelligent automation solutions while driving continuous improvements in machine learning models, NLP performance, and MLOps practices. This is an excellent opportunity for a proactive developer who is passionate about conversational AI, cloud technologies, and delivering innovative AI-powered solutions at scale.
 
 
 
 
 
 
 
 
 
 Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Design, develop, and maintain enterprise-grade conversational AI solutions using RASA Open Source and RASA Pro/X.
 </li>
 <li>
 Develop complex dialogue flows, NLU pipelines, custom actions, stories, and rules.
 </li>
 <li>
 Train, evaluate, fine-tune, and optimize NLP models to improve chatbot performance, intent recognition, entity extraction, and user experience.
 </li>
 <li>
 Build clean, scalable, and maintainable backend services and APIs using Python.
 </li>
 <li>
 Deploy, monitor, and manage AI applications on Google Cloud Platform (GKE, Cloud Run, Compute Engine, Pub/Sub, Vertex AI, Dialogflow, Cloud Speech-to-Text, and Text-to-Speech).
 </li>
 <li>
 Integrate conversational AI solutions with enterprise systems and third-party services.
 </li>
 <li>
 Contribute to CI/CD pipelines, automated testing, model versioning, and MLOps best practices.
 </li>
 <li>
 Analyze conversational data using BigQuery and leverage Cloud Storage for managing training datasets and model artifacts.
 </li>
 <li>
 Collaborate within an Agile development environment and mentor junior team members when needed.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
 </li>
 <li>
 Strong hands-on experience with Python and software engineering best practices.
 </li>
 <li>
 Proven experience developing conversational AI solutions using RASA.
 </li>
 <li>
 Hands-on experience with Google Cloud Platform (GCP) services.
 </li>
 <li>
 Strong understanding of Natural Language Processing (NLP) concepts, including intent classification, entity recognition, dialogue management, and context handling.
 </li>
 <li>
 Experience working with machine learning frameworks such as spaCy, scikit-learn, or Transformers.
 </li>
 <li>
 Proficiency with Git and collaborative software development workflows.
 </li>
 <li>
 Excellent analytical, problem-solving, and communication skills.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills:
 
 
 
 
 
 <ul>
 <li>
 Experience with Docker and Kubernetes.
 </li>
 <li>
 Knowledge of Terraform or other Infrastructure-as-Code tools.
 </li>
 <li>
 Experience implementing CI/CD pipelines and MLOps workflows.
 </li>
 <li>
 Google Cloud certifications, particularly Professional Machine Learning Engineer, are highly desirable.
 </li>
 </ul>
 
 
</div>

AI/ML Developer Level II

Arrow Components

<div>
 
 Position
 
 
 
 Technical Lead &ndash; AI &amp; Machine Learning
 
 
 
 Job Description
 
 
 
 Position Overview
 
 
 As the
 
 Technical Lead &ndash; AI &amp; Machine Learning
 
 at Arrow Electronics, you will play a key role in delivering enterprise AI and machine learning solutions across intelligent products and internal automation platforms. Working under the direction of the AI leadership team, you will translate strategic AI initiatives into scalable, production-ready solutions while providing technical leadership to a team of AI engineers and data scientists.
 
 
 You will lead the implementation of advanced AI systems throughout the complete machine learning lifecycle, including data preparation, model development, experimentation, deployment, monitoring, and continuous optimization. Your expertise will span machine learning, deep learning, neural networks, generative AI, intelligent automation, and large language models.
 
 
 As the technical lead for project execution, you will collaborate closely with software engineering, product management, and data engineering teams to ensure AI solutions are delivered with high quality, scalability, and business impact while mentoring engineers and promoting engineering best practices.
 
 
 Key Responsibilities
 
 
 Technical Execution
 
 
 <ul>
 <li>
 Lead the technical implementation of AI and machine learning initiatives aligned with the organization's AI strategy and roadmap.
 </li>
 <li>
 Translate product and AI leadership vision into scalable technical solutions.
 </li>
 <li>
 Drive engineering best practices, code quality, documentation, and software design across AI projects.
 </li>
 <li>
 Collaborate with AI leadership, product managers, software engineers, and data engineers to successfully deliver AI-powered products.
 
 
 </li>
 </ul>
 Machine Learning &amp; Deep Learning
 
 
 <ul>
 <li>
 Design, develop, and optimize machine learning, deep learning, and neural network models for real-world business applications.
 </li>
 <li>
 Build predictive models, recommendation systems, forecasting models, anomaly detection solutions, classification systems, and intelligent automation workflows.
 </li>
 <li>
 Fine-tune transformer models and other deep learning architectures using modern training techniques.
 
 
 </li>
 </ul>
 Generative AI &amp; Intelligent Systems
 
 
 <ul>
 <li>
 Develop applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, semantic search, embeddings, and prompt engineering.
 </li>
 <li>
 Build intelligent workflows integrating LLMs with enterprise systems, vector databases, and external tools.
 </li>
 <li>
 Evaluate new AI technologies and recommend practical adoption opportunities.
 </li>
 <li>
 Deploy and maintain AI models in production environments.
 
 
 </li>
 </ul>
 Production AI &amp; MLOps
 
 
 <ul>
 <li>
 Ensure AI systems are reliable, secure, efficient, and maintainable.
 
 
 </li>
 </ul>
 Mentorship &amp; Innovation
 
 
 <ul>
 <li>
 Mentor AI engineers and junior machine learning engineers through technical guidance, code reviews, and knowledge sharing.
 </li>
 <li>
 Promote engineering excellence, continuous learning, and adoption of modern AI development practices.
 </li>
 <li>
 Support technical interviews and onboarding of new team members.
 </li>
 <li>
 Stay current with emerging developments in artificial intelligence, machine learning, deep learning, and generative AI.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 6+ years of experience developing and deploying production AI and machine learning solutions.
 </li>
 <li>
 Demonstrated experience leading the technical implementation of AI/ML projects.
 </li>
 <li>
 Strong proficiency in Python and data science libraries including NumPy, pandas, scikit-learn, and related tools.
 </li>
 <li>
 Strong understanding of statistics, machine learning algorithms, feature engineering, and model evaluation.
 </li>
 <li>
 Strong knowledge of neural networks, transformer architectures, and modern deep learning techniques.
 </li>
 <li>
 Experience building applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering.
 </li>
 <li>
 Experience with NLP, document intelligence, semantic search, embeddings, information extraction, and named entity recognition.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field is preferred.
 </li>
 <li>
 Experience deploying AI services using cloud platforms and modern software engineering practices.
 </li>
 <li>
 Familiarity with vector databases, search technologies, and MLOps practices.
 
 
 </li>
 </ul>
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Technical Lead – AI & Machine Learning

<div>
 Responsibilities Cross-Disciplinary Automation
 
 :
 
 Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.
 
 
 Physics-Informed Modeling: Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.
 
 
 
 AI-Enhanced System Engineering
 
 : Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.
 
 
 
 Predictive Project Management
 
 : Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.
 
 
 
 Standards &amp; Compliance:
 
 Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.
 
 
 
 Toolchain Integration
 
 : Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.
 
 
 Key competencies
 
 Technical Skills
 
 
 
 AI and Machine Learning
 
 
 <ul>
 <li>
 Generative AI &amp; LLMs
 </li>
 <li>
 Predictive Modeling
 </li>
 <li>
 Computer Vision
 
 
 </li>
 </ul>
 Data Engineering and Management
 
 
 <ul>
 <li>
 Data Pipeline Construction: Automating the flow of data into AI models.
 </li>
 <li>
 Data Quality Assurance: Cleaning and labeling datasets to ensure the AI isn't learning from "noise."
 
 
 </li>
 </ul>
 
 Process Automation &amp; Integration (MLOps)
 
 
 
 <ul>
 <li>
 Workflow Orchestration: Using tools to connect AI outputs to other R&amp;D software (like ELNs or LIMS).
 </li>
 <li>
 Deployment: Ensuring the AI tools are accessible via user-friendly interfaces.
 
 
 </li>
 </ul>
 
 Programming &amp; Scripting
 
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Javascript / Google Apps Script
 </li>
 <li>
 Google Docs / Sheets functions &amp; automation
 </li>
 <li>
 HTTP rest API's
 
 
 </li>
 </ul>
 Tooling &amp; ALM: ( Plus Knowledge)
 
 
 <ul>
 <li>
 Codebeamer (Requirement Management Tool)
 </li>
 <li>
 Google Cloud Platform
 
 
 </li>
 </ul>
 Automation &amp; Integration concepts
 
 
 <ul>
 <li>
 AI &amp; Data Handling:
 </li>
 <li>
 Basic to intermediate experience with AI tools, APIs, or AI agents
 </li>
 <li>
 Interest in applying AI to engineering processes
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
 </li>
 <li>
 Ability to work autonomously and proactively
 </li>
 <li>
 Analytical mindset with strong problem-solving skills
 </li>
 <li>
 User-oriented mindset (training, support, feedback handling)
 </li>
 <li>
 Time Managment
 
 
 </li>
 </ul>
 Nice to Have
 
 
 Experience with requirement traceability or compliance activities
 
 
 Exposure to AI-assisted automation or low-code/no-code platforms
 
 
 Physics-Informed Machine Learning (PIML)
 
 
 Predictive Project Analytics
 
 
 Understanding of system engineering lifecycle and deliverables
 
 
 
 Aware About Automotive Industry And Embedded Systems.
 
 
 
 Years of Experience 2 to 3 years experience in AI &amp; tools development
</div>

System Design Engineer - AI & Automation, LIGHT

<div>
 Valeo est une entreprise mondiale de haute technologie qui con&ccedil;oit des solutions r&eacute;volutionnaires pour r&eacute;inventer la mobilit&eacute;. Nous sommes un &eacute;quipementier partenaire des constructeurs automobiles et des acteurs de la nouvelle mobilit&eacute; dans le monde entier. Notre vision ? Inventer une mobilit&eacute; plus verte et plus s&ucirc;re, gr&acirc;ce &agrave; des solutions ax&eacute;es sur la conduite intuitive et la r&eacute;duction des &eacute;missions de CO2. Nous sommes leaders dans nos domaines d'activit&eacute; et reconnus comme l'une des plus grandes entreprises innovantes au monde.
 
 
 Responsibilities Cross-Disciplinary Automation
 
 ~
 
 Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.
 
 
 Physics-Informed Modeling~ Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.
 
 
 
 AI-Enhanced System Engineering
 
 ~ Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.
 
 
 
 Predictive Project Management
 
 ~ Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.
 
 
 
 Standards &amp; Compliance~
 
 Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.
 
 
 
 Toolchain Integration
 
 ~ Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.
 
 
 Key competencies
 
 Technical Skills
 
 
 
 AI and Machine Learning
 
 
 <ul>
 <li>
 Generative AI &amp; LLMs
 </li>
 <li>
 Predictive Modeling
 </li>
 <li>
 Computer Vision
 
 
 </li>
 </ul>
 Data Engineering and Management
 
 
 <ul>
 <li>
 Data Pipeline Construction~ Automating the flow of data into AI models.
 </li>
 <li>
 Data Quality Assurance~ Cleaning and labeling datasets to ensure the AI isn't learning from "noise."
 
 
 </li>
 </ul>
 
 Process Automation &amp; Integration (MLOps)
 
 
 
 <ul>
 <li>
 Workflow Orchestration~ Using tools to connect AI outputs to other R&amp;D software (like ELNs or LIMS).
 </li>
 <li>
 Deployment~ Ensuring the AI tools are accessible via user-friendly interfaces.
 
 
 </li>
 </ul>
 Programming &amp; Scripting~
 
 
 <ul>
 <li>
 Python
 </li>
 <li>
 Javascript / Google Apps Script
 </li>
 <li>
 Google Docs / Sheets functions &amp; automation
 </li>
 <li>
 HTTP rest API's
 
 
 </li>
 </ul>
 Tooling &amp; ALM~ ( Plus Knowledge)
 
 
 <ul>
 <li>
 Codebeamer (Requirement Management Tool)
 </li>
 <li>
 Google Cloud Platform
 
 
 </li>
 </ul>
 Automation &amp; Integration concepts
 
 
 <ul>
 <li>
 AI &amp; Data Handling~
 </li>
 <li>
 Basic to intermediate experience with AI tools, APIs, or AI agents
 </li>
 <li>
 Interest in applying AI to engineering processes
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
 </li>
 <li>
 Ability to work autonomously and proactively
 </li>
 <li>
 Analytical mindset with strong problem-solving skills
 </li>
 <li>
 User-oriented mindset (training, support, feedback handling)
 </li>
 <li>
 Time Managment
 
 
 </li>
 </ul>
 Nice to Have
 
 
 Experience with requirement traceability or compliance activities
 
 
 Exposure to AI-assisted automation or low-code/no-code platforms
 
 
 Physics-Informed Machine Learning (PIML)
 
 
 Predictive Project Analytics
 
 
 Understanding of system engineering lifecycle and deliverables
 
 
 
 Aware About Automotive Industry And Embedded Systems.
 
 
 
 Years of Experience 2 to 3 years experience in AI &amp; tools development
 
 
 
 Position~
 
 
 
 AI4all, Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 GTSC Software
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-04-07
 
 
 
 Join Us !
 
 
 Being part of our team, you will join~
 
 
 <ul>
 <li>
 one of the largest global innovative companies, with more than 20,000 engineers working in Research &amp; Development
 </li>
 <li>
 a multi-cultural environment that values diversity and international collaboration
 </li>
 <li>
 more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
 </li>
 <li>
 a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
 
 
 </li>
 </ul>
 More information on Valeo~ https~//www.valeo.com
 
</div>

Explore 108+ Machine learning engineer in Cairo this August. Find roles across top companies and apply now to boost your career.

108 machine learning engineer jobs In Cairo

Machine Learning Engineer

Data Scientist / Senior Machine Learning Engineer

Software Engineer - Machine Learning (SDV), POWER

AI/ML Developer Level II

Technical Lead – AI & Machine Learning

System Design Engineer - AI & Automation, LIGHT

System Design Engineer - AI & Automation, LIGHT