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Capgemini

<div>
 
 About Capgemini
 
 
 
 Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of &euro;22.1 billion.
 
 
 
 Job Description
 
 
 
 <ul>
 <li>
 Design and implement Agentic AI solutions and applications.
 </li>
 <li>
 Lead the end-to-end lifecycle of machine learning and data science delivery engagements, 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>
 Architect and optimize scalable data pipelines and cloud-based infrastructures (Azure, AWS, GCP) to support ML workloads.
 </li>
 <li>
 Collaborate with data engineers to ensure robust data preprocessing, transformation, and storage strategies.
 </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>
 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>
 
 Job Requirements
 
 
 
 <ul>
 <li>
 6-10 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 and delivering AI solution architecture.
 </li>
 <li>
 Strong proficiency in Python, data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and agentic application development libraries (e.g. LangChain, LangGraph).
 </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 (e.g. Docker), and orchestration (Kubernetes).
 </li>
 <li>
 Strong command of Git and collaborative development workflows.
 </li>
 <li>
 Excellent written and verbal communication skills, capable of conveying complex concepts to a variety of audiences.
 </li>
 <li>
 Fluent in Arabic &amp; English, both spoken and written (German is a plus!)
 </li>
 <li>
 Able to listen to and understand customer needs and articulate them as technical requirements to the team.
 </li>
 <li>
 Strong problem-solving abilities and attention to detail.
 </li>
 <li>
 Strategic thinking with the ability to align data science initiatives with business objectives.
 </li>
 <li>
 Strong leadership and team management skills with the ability to inspire and motivate.
 </li>
 <li>
 Ability to work collaboratively in a team environment.
 </li>
 <li>
 Self-motivated with a strong growth mindset.
 </li>
 </ul>
</div>

Senior Data Scientist - AI & ML Engineer

Deloitte

<div>
 
 Deloitte Innovation Hub | AI &amp; Data | Senior AI / ML Engineer, Cairo, Egypt
 
 
 
 
 Connect to your career at Deloitte
 
 
 
 Deloitte, established globally in 1845, is the world&rsquo;s largest and leading professional services firm, providing Audit &amp; Assurance, Tax &amp; Legal and Consulting and related services to public and private clients spanning multiple industries. Present in more than 150 countries, Deloitte is distinct in its ability to help clients solve their most complex problems, from strategy to implementation.
 
 
 Deloitte innovation hub (DIH) is a strategic initiative established by Deloitte North &amp; South Europe (NSE) to support our ambition to become the leading business transformation partner of choice for our clients and to expand and scale our delivery footprint across EMEA. With access to a scaled, diverse, highly skilled, motivated, and engaged workforce, DIH is delivering complex technical solutions for clients&rsquo; most complex business problems, across portfolios that include &lsquo;Strategy &amp; Transactions&rsquo;, &lsquo;Customer&rsquo;, &lsquo;Engineering, AI &amp; Data, &lsquo;Enterprise, Technology &amp; Performance&rsquo; and &lsquo;Cyber&rsquo;. DIH is aiming to become the destination for top talents in Egypt for a long, exciting career.
 
 
 We invest in outstanding people of diverse talents and backgrounds and empower them to achieve more than they could elsewhere. Our work combines advice with action and integrity. We believe that when our clients and society are stronger, so are we. Our organization has grown in scale and diversity, providing services across the region, with our shared culture remaining the same. We aim to help clients realize their ambitions, make a positive difference in society, and maximize the success of our people. This drive fuels the commitment and humanity that run deep through our every action.
 
 
 
 Connect to your opportunity.
 
 
 
 We are seeking committed new talent to join our AI &amp; Data team. Our goal is to work together with our clients to drive innovation and insight from their data, using cutting edge Data Science and Machine Learning techniques alongside Digital Transformation.
 
 
 As a Senior AI/ML Engineer in our team, you will:
 
 
 <ul>
 <li>
 Apply data science and machine learning techniques creatively to solve complex problems.
 </li>
 <li>
 Research and develop innovative solutions.
 </li>
 <li>
 Stay abreast in new machine learning techniques and data technologies.
 </li>
 <li>
 Participate in all phases of the data science lifecycle from PoC to fully tested productionized solutions.
 </li>
 <li>
 Prepare technical documentation.
 </li>
 <li>
 Ensure high-quality delivery of key parts of our engagements working with our senior data scientists.
 </li>
 <li>
 Suggest practical solutions to clients and work to implement these solutions as a part of larger project teams.
 </li>
 <li>
 Assist in the crafting of responses to client proposal requests and in pitching data science projects to client.
 
 
 </li>
 </ul>
 
 Client Engagement
 
 
 
 Your Tasks would include
 
 :
 
 
 
 <ul>
 <li>
 Engage with clients to understand their pain points and requirements.
 </li>
 <li>
 Communicate solutions/propositions effectively back to client/team.
 
 
 </li>
 </ul>
 
 Data Analysis And Pre-processing
 
 
 
 <ul>
 <li>
 Collect and clean large datasets for machine learning projects.
 </li>
 <li>
 Explore data to identify patterns, anomalies, and potential insights.
 </li>
 <li>
 Pre-process data, including feature engineering and normalization.
 
 
 </li>
 </ul>
 
 Algorithm Development
 
 
 
 <ul>
 <li>
 Design, develop, and implement machine learning algorithms.
 </li>
 <li>
 Experiment with various machine learning models and techniques.
 </li>
 <li>
 Optimize algorithms for accuracy, efficiency, and scalability.
 
 
 </li>
 </ul>
 
 Model Training And Evaluation
 
 
 
 <ul>
 <li>
 Train machine learning models using collected data.
 </li>
 <li>
 Perform testing to validate models.
 </li>
 <li>
 Evaluate model performance using appropriate metrics and techniques.
 </li>
 <li>
 Fine-tune models to improve predictive accuracy.
 
 
 </li>
 </ul>
 
 Data Visualization
 
 
 
 <ul>
 <li>
 Create informative data visualizations to communicate insights effectively.
 </li>
 <li>
 Work with visualization libraries like Matplotlib, Seaborn, or data visualization software&rsquo;s like Tableau, PowerBI.
 
 
 </li>
 </ul>
 
 Connect To Your Skills And Professional Experience.
 
 
 
 You're a Natural Problem Solver: Collaboration is at the core of our culture, and we're seeking someone who excels in teamwork and brings out the best in their colleagues. You'll be a brilliant listener, promoting a culture of innovation and knowledge sharing. At Deloitte, we believe in giving our AI/ML Engineers the autonomy they need to excel while upholding our high standards, integrity, and culture.
 
 
 
 Essentials
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Engineering or equivalent
 </li>
 <li>
 3-7 years of experience in Data Science and AI/ML
 </li>
 <li>
 Technical Expertise: Mastery in AI and ML algorithms, frameworks (e.g., TensorFlow, PyTorch), and libraries.
 </li>
 <li>
 Data proficiency: Proficient in data collection, pre-processing, and analysis.
 </li>
 <li>
 Model Mastery: Proven experience in developing and fine-tuning machine learning models.
 
 
 </li>
 </ul>
 
 Desirables
 
 
 
 <ul>
 <li>
 Familiarity with deploying ML frameworks in industry.
 </li>
 <li>
 A strong interest in staying abreast of the latest AI/ML advancements.
 </li>
 <li>
 Project Leadership: Previous experience leading AI/ML initiatives.
 
 
 </li>
 </ul>
 
 Connect to your service line - Technology and Transformation
 
 
 
 Distinctive thinking, deep expertise, and collaborative working. That&rsquo;s what connects us. That&rsquo;s what makes us Deloitte. If you want to help solve some of the biggest challenges around, join us. Together, we&rsquo;ll make an impact that matters.
 
 
 
 Our commitment to you
 
 
 
 Making an impact is more than just what we do: it&rsquo;s why we&rsquo;re here. So we work hard to create an environment where you can experience a purpose you believe in, the freedom to be you, and the capacity to go further than ever before.
 
 
 We want you. The true you. Your own strengths, perspective, and personality. So, we&rsquo;re nurturing a culture where everyone belongs, feels supported and heard, and is empowered to make a valuable, personal contribution. You can be sure we&rsquo;ll take your wellbeing seriously, too. Because it&rsquo;s only when you&rsquo;re comfortable and at your best that you can make the kind of impact you, and we, live for.
 
 
 Your expertise is our capability, so we&rsquo;ll make sure it never stops growing. Whether it&rsquo;s from the complex work you do, or the people you collaborate with, you&rsquo;ll learn every day. Through world-class development, you&rsquo;ll gain invaluable technical and personal skills. Whatever your level, you&rsquo;ll learn how to lead.
 
 
 
 Connect to your next step
 
 
 
 A career at Deloitte is an opportunity to develop in any direction you choose. Join us and you&rsquo;ll experience a purpose you can believe in and an impact you can see. You&rsquo;ll be free to bring your true self to work every day. And you&rsquo;ll never stop growing, whatever your level.
</div>

Deloitte Innovation Hub I Senior AI/ ML Engineer, Cairo, Egypt

Finaira

<div>
 The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives.
 
 
 
 Focus:
 
 End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship
 
 
 
 The difference you will make:
 
 
 
 <ul>
 <li>
 Provide technical leadership, guidance, and mentorship to a team of AI Engineer
 </li>
 <li>
 Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production
 </li>
 <li>
 Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans
 </li>
 <li>
 Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing
 </li>
 <li>
 Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments
 </li>
 <li>
 Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation
 </li>
 <li>
 Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency
 </li>
 <li>
 Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth
 </li>
 <li>
 Act as a primary technical point of contact for stakeholders regarding AI solutions
 </li>
 <li>
 Hands-on contribution to critical code components, architectural design, and complex problem-solving
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 What you will bring to the role:
 
 
 
 
 Education:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred
 
 
 </li>
 </ul>
 
 Experience:
 
 
 
 <ul>
 <li>
 8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end
 
 
 </li>
 </ul>
 
 Technical Skills:
 
 
 
 <ul>
 <li>
 Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras)
 </li>
 <li>
 Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving
 </li>
 <li>
 In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes)
 </li>
 <li>
 Strong architectural skills for building robust, scalable, and maintainable AI infrastructures
 </li>
 <li>
 Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services
 </li>
 <li>
 Excellent understanding of data engineering principles, data governance, and database technologies
 </li>
 <li>
 Ability to evaluate and make sound technical decisions on complex trade-offs
 
 
 </li>
 </ul>
 
 Soft Skills:
 
 
 
 <ul>
 <li>
 Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership
 </li>
 <li>
 Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives
 </li>
 <li>
 Strong mentoring and coaching skills, with a passion for developing the talents of junior team members
 </li>
 <li>
 Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships
 
 
 </li>
 </ul>
 Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.
</div>

Principal AI Engineer

<div>
 
 The Principal AI Engineer provides technical leadership and direction for a team of AI Engineers, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives. Focus: End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship.
 
 
 
 
 
 The difference you will make
 
 <ul>
 <li>
 Provide technical leadership, guidance, and mentorship to a team of AI Engineers.
 </li>
 <li>
 Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production.
 </li>
 <li>
 Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans.
 </li>
 <li>
 Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing.
 </li>
 <li>
 Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments.
 </li>
 <li>
 Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation.
 </li>
 <li>
 Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency.
 </li>
 <li>
 Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth.
 </li>
 <li>
 Act as a primary technical point of contact for stakeholders regarding AI solutions.
 </li>
 <li>
 Hands-on contribution to critical code components, architectural design, and complex problem-solving.
 </li>
 </ul>
 
 
 
 
 What you will bring to the role
 
 
 Education: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred.
 
 
 
 
 
 Experience: 8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end.
 
 
 
 
 
 Technical Skills:
 
 <ul>
 <li>
 Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras).
 </li>
 <li>
 Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving.
 </li>
 <li>
 In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes).
 </li>
 <li>
 Strong architectural skills for building robust, scalable, and maintainable AI infrastructures. o Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services.
 </li>
 <li>
 Excellent understanding of data engineering principles, data governance, and database technologies.
 </li>
 <li>
 Ability to evaluate and make sound technical decisions on complex trade-offs.
 </li>
 </ul>
 
 
 
 
 Soft Skills:
 
 <ul>
 <li>
 Strong ownership and accountability for assigned work.
 </li>
 <li>
 Clear and professional verbal and written communication.
 </li>
 <li>
 Effective time management and task prioritization.
 </li>
 <li>
 Analytical thinking and problem-solving skills.
 </li>
 <li>
 Ability to work independently, collaborate effectively and mentor junior team members.
 </li>
 <li>
 Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
 </li>
 <li>
 Adaptability and learning agility in a fast-paced environment.
 </li>
 <li>
 Strong attention to detail and a commitment to quality.
 </li>
 <li>
 Receptiveness to feedback and continuous improvement mindset.
 </li>
 </ul>
</div>

York Towers

<div>
 Dwelleo is a Saudi AI-powered PropTech platform redefining how real estate decisions are made. From buying and renting to selling and investing, we combine verified data, intelligent insights, and complete transparency &mdash; empowering users to understand the market clearly and make confident decisions at every step.
 
 
 
 About Dwelleo
 
 
 
 Dwelleo is an AI-powered real estate marketplace transforming how people search, buy, sell, and rent properties across Saudi Arabia.
 
 
 The platform combines machine learning, intelligent discovery tools, and data-driven insights to connect buyers, renters, brokers, and developers through a seamless, scalable digital experience.
 
 
 At its core, Dwelleo embeds AI directly into the product &mdash; powering pricing, recommendations, search, and decision-making across the entire property journey.
 
 
 
 About The Role
 
 
 
 You'll work across the full AI surface area of a live product. Your work will span classical ML (pricing, forecasting) and modern LLM systems (agents, RAG, voice), with real engineering expectations around reliability, observability, and production quality. Research here is always in service of shipping &mdash; experimentation exists to accelerate delivery, not replace it.
 
 
 You'll work within a dual-track Agile structure: a
 
 Research sprint
 
 for experimentation and model development, and an
 
 Engineering sprint
 
 for deployment, integration, and reliability work. You'll contribute to both.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Ship predictive models for property price estimation, rent forecasting, and ROI analysis &mdash; from feature engineering through production deployment on AWS ECS with canary release practices
 </li>
 <li>
 Build and maintain LLM-powered multi-agent systems, including deterministic state machines, scoring engines, guardrail layers, and escalation logic that runs reliably at scale
 </li>
 <li>
 Develop and improve RAG pipelines with vector-based retrieval (FAISS, pgvector) for property search and AI-assisted advisory features
 </li>
 <li>
 Expose AI capabilities as FastAPI microservices with autoscaling, versioning, and production-grade reliability
 </li>
 <li>
 Integrate and improve STT/TTS speech pipelines connected to telephony infrastructure &mdash; Arabic dialect support is a meaningful plus
 </li>
 <li>
 Own observability across the stack: drift detection, latency monitoring, alerting, and model performance dashboards
 </li>
 <li>
 Collaborate closely with product and engineering across both sprint tracks, translating research outcomes into shippable systems
 
 
 </li>
 </ul>
 
 Required
 
 
 
 
 What we're looking for
 
 
 
 <ul>
 <li>
 3&ndash;6 years of hands-on experience in ML engineering, AI engineering, or a closely related role &mdash; with at least some of that time shipping to production
 </li>
 <li>
 Strong Python skills with a track record of production deployment (not just notebooks)
 </li>
 <li>
 Solid ML fundamentals: supervised learning, gradient boosting (XGBoost / LightGBM), feature engineering, model evaluation, and retraining workflows
 </li>
 <li>
 Hands-on experience with LLMs (OpenAI, Anthropic, or open-source models) and practical RAG pipeline implementation
 </li>
 <li>
 Experience building and deploying ML microservices using FastAPI
 </li>
 <li>
 Working knowledge of CI/CD for ML workloads &mdash; you've set up or maintained pipelines using tools like GitHub Actions, MLflow, or equivalent
 </li>
 <li>
 Comfortable working in English; Arabic is not required but welcome
 
 
 </li>
 </ul>
 
 Nice To Have
 
 
 
 <ul>
 <li>
 STT/TTS integration or voice pipeline engineering &mdash; Arabic dialect experience is a strong plus
 </li>
 <li>
 AWS hands-on experience: ECS, S3, RDS
 </li>
 <li>
 Familiarity with geospatial data and similarity search (Ball Tree, FAISS, pgvector)
 </li>
 <li>
 Background in lead scoring, content moderation, or recommendation systems
 </li>
 <li>
 Experience with MLflow, experiment tracking, or model registry workflows
 </li>
 <li>
 Real estate or PropTech domain exposure
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 <ul>
 <li>
 Location: Fully remote
 </li>
 <li>
 Team: You'll report directly to the AI Team Lead
 </li>
 <li>
 Direct ownership of production AI systems with measurable user and business impact
 </li>
 <li>
 A technically ambitious environment working at the intersection of AI and one of the region's most active real estate markets
 </li>
 </ul>
</div>

AI Engineer

Quality Standards for Information Technology - QSIT

<div>
 
 
 Job Responsibilities:
 
 
 <ul>
 <li>
 Design, develop, and optimize AI/ML solutions for real business use cases.
 </li>
 <li>
 Build and evaluate machine learning, deep learning, and generative AI models.
 </li>
 <li>
 Analyze and preprocess structured and unstructured data to support model development and solution quality.
 </li>
 <li>
 Validate model performance, reliability, scalability, and production readiness.
 </li>
 <li>
 Ensure AI solutions align with enterprise standards for maintainability, quality, and governance.
 </li>
 <li>
 Design and implement LLM-based and Generative AI solutions, including RAG pipelines, prompt engineering, retrieval optimization, and evaluation.
 </li>
 <li>
 Work with embeddings, vector search, reranking, and enterprise knowledge integration patterns.
 </li>
 <li>
 Support use cases such as document intelligence, AI assistants, chatbots, search augmentation, and decision-support solutions.
 </li>
 <li>
 Own AI solution delivery from requirement analysis through deployment, integration, and handover.
 </li>
 <li>
 Collaborate with software, data, and platform teams to integrate AI capabilities into enterprise platforms and APIs.
 </li>
 <li>
 Support monitoring, optimization, and post-go-live improvement of AI services.
 </li>
 <li>
 Apply MLOps / LLMOps practices for reproducibility, deployment automation, monitoring, and lifecycle management.
 </li>
 <li>
 Support technical proposal development, bid responses, and client-facing AI solution discussions when required.
 </li>
 <li>
 Contribute to technical presentations, solution write-ups, and AI capability positioning.
 </li>
 <li>
 Provide technical insight during opportunity shaping and feasibility assessments.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in Computer Science, AI, Data Science, Computer Engineering, or related field.
 </li>
 <li>
 From 4&ndash;6 years of hands-on experience delivering end-to-end AI/ML solutions in real business environments (not just PoCs/research).
 </li>
 <li>
 Strong Python skills; hands-on with PyTorch, TensorFlow, and Scikit-learn.
 </li>
 <li>
 Experience in data preprocessing, feature engineering, model evaluation, and optimization.
 </li>
 <li>
 Practical experience with Generative AI, LLMs, RAG, embeddings, and vector databases.
 </li>
 <li>
 Familiar with prompt engineering, LLM evaluation, guardrails, and inference optimization.
 </li>
 <li>
 Experience with MLOps/LLMOps (deployment, monitoring, versioning, lifecycle).
 </li>
 <li>
 Cloud experience: Azure AI / Azure OpenAI preferred; AWS/GCP a plus.
 </li>
 <li>
 Experience with APIs, microservices, enterprise integration, and Docker/containers.
 </li>
 <li>
 Experience in domains like NLP, document intelligence, CV, forecasting, recommendations, or conversational AI.
 </li>
 <li>
 Strong analytical, communication, and cross-functional collaboration skills; leadership/mentoring mindset.
 </li>
 <li>
 Proven delivery of deployed AI/ML solutions.
 </li>
 <li>
 Provide project examples with: domain/client, AI approach, role, and deployment environment.
 </li>
 <li>
 Show involvement in deployment, handover, and post-go-live support/optimization.
 </li>
 </ul>
 
 
</div>

Senior AI Engineer

Valeo

<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.
 
 
 <ul>
 <li>
 End-to-End AI/ML Solution Delivery
 </li>
 <li>
 Design &amp; Develop~ Design, develop, industrialize, and deploy advanced predictive and machine learning models (e.g., supervised/unsupervised, scoring, NLP, recommendation &amp; personalization systems,classification, regressions and diagnostic).
 </li>
 <li>
 Build &amp; Innovate~ Build, maintain, and improve robust, scalable data and ML pipelines, from exploration to production (API, CI/CD, MLOps). Construct and innovate with Generative AI systems (LLMs, RAG, fine-tuning) to enhance product features and internal processes.
 </li>
 <li>
 Ensure Quality~ Guarantee solutions are robust, scalable, and production-ready by applying best practices in software engineering and MLOps (e.g., containerization, monitoring, versioning).
 </li>
 <li>
 Own &amp; Deploy~ Own your models end-to-end, from idea generation and prototyping to deployment, monitoring, A/B testing, and continuous improvement. Drive the integration of models into production-ready pipelines, establishing and managing version control, validation, and automated testing strategies.
 </li>
 <li>
 Technical Strategy &amp; Leadership
 </li>
 <li>
 Problem Framing~ Frame use cases with business teams, validate data availability, and use rigorous analysis to break down ambiguous business questions into testable hypotheses and concrete data science projects. Define success metrics (KPIs) upfront to ensure every project has a measurable business impact.
 </li>
 <li>
 Technology Assessment~ Lead "make-or-buy" decisions by evaluating the trade-offs between building proprietary models versus integrating third-party AI services, always aligning with business objectives for speed, cost, and long-term value.
 </li>
 <li>
 Mentorship &amp; Standardization~ Act as a technical reference, providing leadership and mentorship to junior data scientists through code reviews and knowledge sharing. Drive technical excellence by standardizing frameworks and improving our technical stack, modeling approaches, and deployment practices.
 </li>
 <li>
 Innovation~ Stay ahead of market trends and conduct active research on the latest advancements in AI/ML to identify and propose innovative approaches and new use cases. This includes attending conferences,, and participating in meetups and internal learnshops.
 </li>
 <li>
 Collaboration &amp; Influence
 </li>
 <li>
 Data-Driven Collaboration~ Act as the analytical authority within cross-functional teams (Product, Engineering, Business). Challenge existing assumptions with data, guide strategic decisions with analytical evidence, and ensure model outputs are directly integrated into business workflows.
 </li>
 <li>
 Insightful Communication~ Go beyond just presenting results. Clearly explain the "why" behind your model's logic, its limitations (e.g., biases, confidence levels), and the trade-offs between different analytical approaches to both technical and executive audiences.
 </li>
 <li>
 Actionable Visualization~ Create clear dashboards and visualizations that tell a story with the data, empowering stakeholders to make data-informed decisions independently.
 </li>
 <li>
 Cross-Functional Leadership~ Lead collaboration with IT and Data Engineering teams to enhance data accessibility, harmonization, pipeline robustness, and streamline model deployment.
 </li>
 <li>
 Data Strategy~ Evaluate data availability, coverage, and quality, proposing pragmatic approaches for calibration, substitution, or enrichment when datasets are incomplete or imperfect.
 
 
 </li>
 </ul>
 
 
 
 Professional
 
 
 Experience
 
 
 
 
 
 We are looking for a candidate who embodies three core strengths~
 
 
 <ul>
 <li>
 Technical &amp; Execution Excellence You are a master builder who ships robust, production-grade solutions.
 </li>
 <li>
 After a master degree and PhD , you bring 5+ years of applied experience as a Data Scientist, with a proven track record of taking complex Machine Learning projects from initial POC to full production deployment.
 </li>
 <li>
 Your experience comes from a fast-paced, commercial environment (such as E-commerce, FinTech, Online Travel, SaaS, or modern Tech Consulting), where you have successfully built and shipped models for dynamic pricing, demand forecasting, or resource optimization.
 </li>
 <li>
 Your technical toolkit is extensive, with an excellent mastery of Python and its core data science libraries (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, pandas, NumPy).
 </li>
 <li>
 You have strong knowledge of the full MLOps and Data Engineering lifecycle, including SQL, containerization (Docker), workflow orchestration (Airflow), CI/CD, and model deployment/serving (MLflow, Kubernetes, REST APIs).
 </li>
 <li>
 You have a deep understanding of Generative AI architectures and workflows (embeddings, RAG, fine-tuning) and have experience with GenAI/LLM projects.
 </li>
 <li>
 You are adept at creating clear, insightful visualizations using tools like Looker, Tableau, or Power BI and applying Agile/scrum methodologies to deliver results iteratively.
 </li>
 <li>
 You have hands-on experience working with large-scale datasets in cloud environments (e.g., AWS, GCP).
 </li>
 <li>
 Strategic &amp; Business Acumen You think like a business owner and translate complex data into tangible value.
 </li>
 <li>
 You have a proven ability to deconstruct ambiguous business problems into a clear analytical framework, defining testable hypotheses and the KPIs that will measure success.
 </li>
 <li>
 You demonstrate strong project management skills, taking ownership of the entire project lifecycle to ensure solutions are delivered on time and create measurable business impact.
 </li>
 <li>
 You practice statistical rigor, going beyond model accuracy to validate choices, quantify uncertainty, and ensure the reliability and fairness of your results in a real-world context.
 </li>
 <li>
 You have led root-cause investigations, using data to diagnose why business metrics deviate from expectations and recommending a clear solution.
 </li>
 <li>
 You demonstrate exceptional business impact translation, turning complex model outputs into a compelling narrative that influences leadership-level decisions.
 </li>
 <li>
 Leadership &amp; Collaborative Influence You are a natural coach and communicator who elevates the entire team.
 </li>
 <li>
 You possess strong leadership and mentoring skills with a genuine passion for sharing knowledge, helping others grow, and fostering a collaborative team environment.
 </li>
 <li>
 Your communication skills are excellent, giving you the ability to tell a compelling story with data and distill complex topics into simple, clear explanations for any audience.
 </li>
 <li>
 You have a proactive, autonomous, and results-oriented mindset. You are intellectually curious, pragmatic, and thrive in a fast-paced, collaborative setting.
 </li>
 <li>
 You have the business acumen to understand complex challenges and translate them into adapted technical solutions.
 
 
 </li>
 </ul>
 
 Position~
 
 
 
 Engineering Disciplines
 
 
 
 D&eacute;partement~
 
 
 
 Software Development
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-02-22
 
 
 
 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>

Senior AI Technical Lead, Valeo Service

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