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machine learning engineer

Unifonic

<div>
 
 Job Description
 
 
 
 Proudly voted a Great Place to Work&reg;, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customer-centric companies.
 
 
 We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we&rsquo;re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!
 
 
 
 Meet the team!
 
 
 
 Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic&rsquo;s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cutting-edge communication and engagement solutions, we want you on our team.
 
 
 As a Senior Machine Learning (AI) Engineer, you will be responsible for designing, developing, and deploying advanced machine learning solutions across various domains, including NLP, Text Classification, RAG, LLMs, Recommender engines, and Anomaly detection. This role involves end-to-end project ownership, from data preprocessing to the creation of service APIs, and offers opportunities to work on cutting-edge AI technologies.
 
 
 
 Help Us Shape The Future Of Communication By
 
 
 
 <ul>
 <li>
 Leading the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures.
 </li>
 <li>
 Architecting and implementing RAG systems, combining large language models (LLMs) with robust retrieval mechanisms to improve the accuracy, factual grounding, and interpretability of generated content.
 </li>
 <li>
 Applying advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction.
 </li>
 <li>
 Researching, evaluating, and integrating state-of-the-art NLP models and RAG frameworks (e.g., Transformers, BERT, GPT variants, Vector Databases, Semantic Search).
 </li>
 <li>
 Mentoring junior team members on the team, sharing knowledge, and advising the best machine learning and software engineering practices and approaches.
 </li>
 <li>
 Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products.
 </li>
 <li>
 Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks.
 </li>
 <li>
 Staying up to date with the latest machine learning research papers, and AI trends (i.e. Generative AI).
 </li>
 <li>
 Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns, in real-time, near-real-time, or batch processing mode.
 </li>
 <li>
 Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
 </li>
 <li>
 Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA.
 </li>
 <li>
 Reviewing the code of other team members and suggesting improvements to ensure the SOLID principles and clean architecture.
 </li>
 <li>
 Assisting in the project documentation and demos.
 
 
 </li>
 </ul>
 
 Job Requirements
 
 
 
 
 What you'll bring:
 
 
 
 <ul>
 <li>
 Proven experience designing and implementing RAG systems, including familiarity with various retrieval strategies (e.g., BM25, dense retrieval, hybrid approaches) and knowledge graph integration.
 </li>
 <li>
 Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar tools for building and managing autonomous agents.
 </li>
 <li>
 Deep expertise in various NLP techniques and models, including but not limited to:
 
 
 </li>
 </ul>
 Transformer architectures (e.g., BERT, GPT, T5, LLama, Mistral)
 
 
 Large Language Models (LLMs) and their fine-tuning/adaptation
 
 
 Vector embeddings and similarity search
 
 
 Text classification, named entity recognition (NER), sentiment analysis, summarization, and question answering.
 
 
 <ul>
 <li>
 Hands-on 3-5 years of relevant work experience as a Machine Learning Engineer.
 </li>
 <li>
 Hands-on 3+ years of experience with Python.
 </li>
 <li>
 Excellent analytical abilities, with the capacity to collect, organize, and analyze large datasets to glean valuable insights.
 </li>
 <li>
 End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
 </li>
 <li>
 Ability to write world-class code in Python (SOLID principles), considering the best software engineering fundamentals, i.e. data structures, algorithms, and data modeling
 </li>
 <li>
 Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
 </li>
 <li>
 Familiarity with MLOps best practices, e.g. Model deployment and reproducible research.
 </li>
 <li>
 Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
 </li>
 <li>
 Basic knowledge of Kubernetes and Docker is nice to have.
 </li>
 <li>
 Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.
 </li>
 <li>
 Experience with the Hugging Face libraries (i.e. transformers).
 </li>
 <li>
 Experience fine-tuning pre-trained models and using vector search to enhance LLMs results.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques.
 </li>
 <li>
 Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
 </li>
 <li>
 Familiar with Agile methodologies i.e. scrum and kanban.
 </li>
 <li>
 Ability to develop high-level architecture and low-level design, End-to-end for a specific project.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is a plus.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques is nice to have.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is nice to have.
 </li>
 <li>
 General knowledge of Data warehouse tools e.g. Vertica is a plus.
 </li>
 <li>
 A Bachelor&rsquo;s degree in a relevant field. (e.g. Computer Science, Computer Engineering, Software, etc).
 </li>
 <li>
 Excellent communication and collaboration skills.
 </li>
 <li>
 Good level of spoken and written Arabic and English.
 
 
 </li>
 </ul>
 
 As a Unifone you will receive a range of benefits:
 
 
 
 <ul>
 <li>
 Competitive salary and bonus.
 </li>
 <li>
 Unifonic share scheme (we are all owners!).
 </li>
 <li>
 30 holiday days after the first anniversary.
 </li>
 <li>
 Your Birthday off!
 </li>
 <li>
 Spend up to 25 days per year working from anywhere in the world!
 </li>
 <li>
 Paid leave for new parents.
 </li>
 </ul>
</div>

Senior Machine Learning Engineer

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

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

Deloitte

<div>
 
 Deloitte Innovation Hub | AI &amp; Data | Senior AI / ML Engineer, Cairo, Egypt
 
 
 
 
 Connect to your career at Deloitte
 
 
 
 Deloitte, established globally in 184
 
 
 
 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, Strategic Risk &amp; Transactions Advisory and Technology &amp; Transformation 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 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>
 Experience 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 and Power BI.
 
 
 </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&rsquo;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.
 
 
 Deloitte innovation hub (DIH) is a strategic initiative established 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>
 
 
 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

mylo

<div>
 
 mylo
 
 is a fintech platform dedicated to helping millions of people and businesses thrive by providing accessible and responsible financial solutions. Whether you're purchasing a mobile phone, a new jacket, a flight ticket, a comfy couch, or even covering school tuition, mylo enables you to buy now and pay later at thousands of points of sale across Egypt. Born out of B.TECH&mdash;Egypt's leading electronics and appliances retailer with over 27 years of experience in offering buy now, pay later solutions&mdash;mylo brings a legacy of trust and innovation to the fintech space. All mylo products are fully Sharia-compliant, ensuring ethical and inclusive financial practices.
 
 
 We are seeking a passionate and experienced
 
 Senior Data Engineer
 
 to join our team within the Fintech domain. This role is ideal for someone who thrives in a fast-paced environment and is excited to design, build, and scale secure, high-performing infrastructure to support a range of financial products.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Multi-Domain Technical Strategy: Lead the development of ML solutions across diverse contexts, ensuring that models for Credit Risk, Pricing Elasticity, and Collection Optimization utilize shared infrastructure efficiently
 </li>
 <li>
 MLOps Architecture: Champion the adoption of modern Model Serving frameworks and Feature Stores. Design workflows that ensure feature consistency between training and real-time inference
 </li>
 <li>
 Engineering Standards: Establish rigorous standards for Data Versioning, experiment tracking, and Hyperparameter Optimization, ensuring all research is reproducible and production-ready
 </li>
 <li>
 Production Deployment: Oversee the transition of models from notebook environments to low-latency production APIs. Ensure models are wrapped, containerized, and integrated seamlessly with backend services
 </li>
 <li>
 Mentorship: Guide the team in best practices for Python software engineering, including testing strategies, code structure, and performance optimization
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Experience: 4+ years in Data Science with a strong emphasis on production engineering. Experience in Fintech, Lending, or Risk is highly preferred
 </li>
 <li>
 ML Proficiency: Deep understanding of both classical machine learning (Gradient Boosting, Statistical Models) and Deep Learning frameworks
 </li>
 <li>
 Production Engineering: Proven track record of deploying models in real-time environments. Familiarity with the concepts of Feature Stores and Model Registries is essential
 </li>
 <li>
 Technical Stack: Expert-level Python skills. Strong proficiency in SQL and relational database design
 </li>
 <li>
 Strategic Thinking: Ability to translate complex business KPIs (e.g., reducing Non-Performing Loans) into technical ML roadmaps
 </li>
 </ul>
</div>

Senior Data Scientist

Cegedim

<div>
 
 Votre Mission Chez Cegedim
 
 
 
 Join us in building the infrastructure that powers next-generation AI solutions.At Cegedim Academy, we're looking for passionate MLOps Engineering Interns to work alongside experienced mentors and talented peers on real-world AI and machine learning platforms. As part of the internship, you'll contribute to building scalable, reliable, and production-ready systems that support the deployment and operation of AI solutions.This is a hybrid, fast-paced environment where innovation, collaboration, and continuous learning are encouraged. You'll gain hands-on experience with modern cloud and MLOps technologies while helping deliver AI systems at scale.
 
 
 What You'll Do
 
 
 <ul>
 <li>
 Build and maintain machine learning deployment pipelines
 </li>
 <li>
 Automate model training, testing, and deployment workflows
 </li>
 <li>
 Implement CI/CD practices for machine learning applications
 </li>
 <li>
 Monitor model performance, reliability, and data drift in production
 </li>
 <li>
 Manage cloud infrastructure supporting AI workloads
 </li>
 <li>
 Improve observability, governance, and reproducibility of ML systems
 </li>
 <li>
 Collaborate with AI Engineers, Software Engineers, and mentors throughout the project lifecycle
 </li>
 <li>
 Learn industry best practices for operating machine learning systems
 
 
 </li>
 </ul>
 What We're Looking For
 
 
 Currently pursuing or recently completed (2025 or 2026) a degree in:
 
 
 <ul>
 <li>
 Computer Science
 </li>
 <li>
 Computer Engineering
 </li>
 <li>
 Artificial Intelligence
 </li>
 <li>
 Data Science or related fields
 
 
 </li>
 </ul>
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Strong programming skills in Python
 </li>
 <li>
 Understanding of software engineering and DevOps fundamentals
 </li>
 <li>
 Familiarity with Docker and containerization concepts
 </li>
 <li>
 Knowledge of CI/CD pipelines and version control systems
 </li>
 <li>
 Interest in cloud computing and machine learning operations
 </li>
 <li>
 Familiarity with Kubernetes, MLflow, Airflow, GitHub Actions, GitLab CI, AWS, Azure, or GCP is a plus
 
 
 </li>
 </ul>
 
 Soft Skills
 
 
 
 <ul>
 <li>
 Strong teamwork, communication, and problem-solving skills
 </li>
 <li>
 Curiosity, initiative, and a willingness to learn
 </li>
 <li>
 Ability to work in a collaborative environment
 
 
 </li>
 </ul>
 Why Join Us?
 
 
 <ul>
 <li>
 Work on real-world AI infrastructure and deployment challenges
 </li>
 <li>
 Receive mentorship from experienced professionals
 </li>
 <li>
 Gain practical experience with modern MLOps tools and cloud platforms
 </li>
 <li>
 Collaborate in a supportive and innovative environment
 </li>
 <li>
 Build skills that prepare you for a career in MLOps and Cloud Engineering
 </li>
 </ul>
</div>

MLOps Engineering Intern

LSEG

<div>
 Job Summary:
 
 
 As a Junior Data Scientist, you will assist in delivering data-driven insights and solutions under the guidance of senior data scientists. This role is focused on applying basic machine learning and data analysis techniques to assist in developing solutions that address customer needs. You will collaborate with multi-functional teams, learning from experienced professionals and helping implement data science-driven products, particularly focusing on data preparation, model implementation, and data analysis tasks.
 
 
 Role &amp; Responsibilities:
 
 
 <ul>
 <li>
 Assist in the development and deployment of machine learning models under the guidance of senior data scientists.
 </li>
 <li>
 Apply basic machine learning techniques, including data preprocessing, feature engineering, and model evaluation, to solve business problems.
 </li>
 <li>
 Collaborate with the team to gather and analyze data, ensuring data quality and consistency.
 </li>
 <li>
 Support the creation of dashboards, reports, and data visualizations to communicate findings.
 </li>
 <li>
 Work with senior team members to understand client requirements and contribute to the design and implementation of data science solutions.
 </li>
 <li>
 Perform exploratory data analysis (EDA) to understand data patterns and trends.
 </li>
 <li>
 Assist in the maintenance and updating of models and algorithms in production.
 </li>
 <li>
 Develop scripts for automating data processing tasks and workflows.
 
 
 </li>
 </ul>
 Qualifications and Experience Required:
 
 
 <ul>
 <li>
 3-5 years experience in data science, machine learning, or a related field, ideally in a financial industry or familiar with finance.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Engineering, Data Science, or a related field.
 </li>
 <li>
 Basic understanding of machine learning algorithms and their applications.
 </li>
 <li>
 Proficiency in Python with knowledge of libraries such as Pandas, NumPy, and scikit-learn for data analysis and model building.
 </li>
 <li>
 Familiarity with SQL for querying relational databases and performing data manipulation.
 </li>
 <li>
 Understanding of data preprocessing techniques, including handling missing data, scaling, and encoding.
 </li>
 <li>
 Basic knowledge of cloud platforms (AWS, GCP, or Azure) and machine learning frameworks such as TensorFlow or PyTorch.
 </li>
 <li>
 Ability to learn quickly and apply new concepts in data science.
 </li>
 <li>
 Strong analytical and problem-solving skills, with the ability to communicate findings effectively.
 </li>
 <li>
 A passion for learning and staying updated with the latest developments in data science and machine learning.
 </li>
 <li>
 Experience with data visualization tools like Tableau, Power BI, or Matplotlib.
 </li>
 <li>
 Familiarity with NoSQL databases like MongoDB or Cassandra.
 </li>
 <li>
 Knowledge of basic NLP techniques for text data analysis.
 </li>
 <li>
 Interest in gaining exposure to deep learning frameworks like TensorFlow and PyTorch.
 </li>
 <li>
 Interest in gaining exposure to LLMs and agentic frameworks
 
 
 </li>
 </ul>
 LSEG is committed to encouraging a diverse, equitable, an inclusive work environment, ensuring equal opportunities for all employees, regardless of their background. We offer great employee benefits to make sure everyone performs to the best of their abilities. We offer a hybrid working model.
 
 
 
 Career Stage:
 
 
 
 Senior Associate
 
 
 
 London Stock Exchange Group (LSEG) Information:
 
 
 
 Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.
 
 
 LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.
 
 
 Our purpose is the foundation on which our culture is built. Our values of
 
 Integrity, Partnership
 
 ,
 
 Excellence
 
 and
 
 Change
 
 underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.
 
 
 Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
 
 
 We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone&rsquo;s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
 
 
 You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.
 
 
 LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
 
 
 Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it&rsquo;s used for, and how it&rsquo;s obtained, your rights and how to contact us as a data subject.
 
 
 If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.
</div>

Junior Data Scientist

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