accountant – accounts receivable (junior)

data engineer

senior network engineer

ai platform engineer

aws devops senior

senior backend engineer

senior 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>
 <li>
 LinkedIn learning license.
 </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>

Implicit

<div>
 Innovation is at the heart of what we do. At Implicit, natural language processing, machine learning, and data are at the core of our work.
 
 
 We are seeking a software engineer to join our team in Cairo. As a Software Engineer at Implicit, you will work closely with our data science and product teams to build the next-generation AI knowledge engine.
 
 
 Join Implicit and come work with some of the world's most talented data scientists, engineers, and thought leaders.
 
 
 
 As a Software Engineer, you will:
 
 
 
 <ul>
 <li>
 Design, build and test new services to support our products.
 </li>
 <li>
 Ensure the performance, quality, and responsiveness of the services.
 </li>
 <li>
 Ensure high code and design quality that fulfills business requirements and good design aspects (scalability, fault tolerance).
 </li>
 <li>
 Participate in technical decision making with senior leadership and team members by:
 </li>
 <ul>
 <li>
 Supporting technical estimations and effort sizing.
 </li>
 <li>
 Supporting the culture of technical excellence and zero technical debt via code &amp; design reviews
 </li>
 <li>
 Establishing code guidelines and reviewing team members' PRs.
 </li>
 </ul>
 <li>
 Stay up to date with the latest industry trends in software and cloud solutions.
 
 </li>
 </ul>
 
 Qualifications:
 
 
 
 <ul>
 <li>
 A minimum of 5+ years of relevant programming experience is a must.
 </li>
 <li>
 Experience with Java 8, 11, with good object-oriented design and programming skills.
 </li>
 <li>
 Working experience developing REST APIs.
 </li>
 <li>
 Experience with Spring framework (boot, security, data, test).
 </li>
 <li>
 Experience with SQL databases, preferably Postgres.
 </li>
 <li>
 Experience with unit testing, integration test and TDD.
 </li>
 <li>
 Solid understanding of algorithms, data structures, and complexity.
 </li>
 <li>
 Good command of Git and team workflows.
 </li>
 <li>
 Professional-level written and spoken English.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Experience with Python scripting language.
 </li>
 <li>
 Experience with graph databases, preferably Neo4j.
 </li>
 <li>
 Good knowledge of containerization concepts (e.g. Docker and Kubernetes).
 </li>
 <li>
 Experienced with any of the cloud platforms (Azure, GCP, or Amazon).
 </li>
 <li>
 Familiarity with Agile project management methodologies.
 </li>
 <li>
 Good knowledge of the architectural patterns used in data pipelines. (Event-driven, Micro-services, Event sourcing, ...).
 
 
 </li>
 </ul>
 
 What we Offer:
 
 
 
 <ul>
 <li>
 Participate in building world-class products and applications for our leading-edge AI platform
 </li>
 <li>
 Join a fun, diverse team of the world's most talented professionals
 </li>
 <li>
 Competitive compensation packages
 </li>
 <li>
 Highest tier social insurance and local health insurance
 </li>
 <li>
 Flexible and open leave policy
 </li>
 <li>
 Flexible working hours
 </li>
 </ul>
</div>

Java Software Engineer- Part Time

Interact Technology Solutions

<div>
 
 Job Summary
 
 
 
 The
 
 Senior AI Data Engineer
 
 is responsible for designing, building, and optimizing enterprise-scale data and AI infrastructure to support machine learning models, generative AI applications, and real-time analytics. The role drives the development of end-to-end data pipelines, from ingestion to production-ready AI data products, ensuring scalability, performance, and compliance across multi-cloud environments.
 
 
 
 Accountability &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable ETL/ELT data pipelines using modern data engineering tools (e.g., Apache Spark, dbt).
 </li>
 <li>
 Architect and implement Lakehouse data platforms (Delta Lake, Apache Iceberg, Apache Hudi) following Medallion architecture (Bronze/Silver/Gold).
 </li>
 <li>
 Develop real-time streaming pipelines using Apache Kafka, Apache Flink, and Spark Structured Streaming.
 </li>
 <li>
 Build and optimize AI/GenAI data pipelines for LLM training, fine-tuning, and inference (tokenization, dataset curation, prompt engineering datasets).
 </li>
 <li>
 Design and implement Retrieval-Augmented Generation (RAG) pipelines, including embedding workflows and vector database integration.
 </li>
 <li>
 Manage feature stores for real-time and batch machine learning use cases.
 </li>
 <li>
 Integrate data pipelines with AI/ML platforms (Databricks MLflow, Azure ML, AWS SageMaker, Vertex AI, OpenAI/Azure OpenAI).
 </li>
 <li>
 Implement data orchestration workflows using Apache Airflow or similar tools with CI/CD pipelines.
 </li>
 <li>
 Ensure data quality, governance, and security using frameworks such as Great Expectations and data catalog tools.
 </li>
 <li>
 Deploy and manage infrastructure using Infrastructure-as-Code tools (Terraform, Bicep, CDK).
 </li>
 <li>
 Collaborate with Data Scientists, ML Engineers, and Solution Architects to deliver production-ready AI solutions.
 </li>
 <li>
 Lead technical design decisions, mentor junior engineers, and contribute to data platform strategy.
 </li>
 <li>
 Maintain documentation, data contracts, and operational runbooks for all pipelines.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 1
 
 &ndash; Required Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.
 </li>
 <li>
 4&ndash;5 years of experience in data engineering, with strong exposure to AI/ML data infrastructure.
 </li>
 <li>
 Proven experience building scalable data pipelines and working with large-scale datasets.
 </li>
 <li>
 Hands-on experience with AI/ML platforms and modern data architectures.
 </li>
 <li>
 Experience in regulated industries (e.g., Banking, Telecom, Healthcare) is a plus.
 </li>
 <li>
 Strong problem-solving, analytical thinking, and communication skills.
 </li>
 <li>
 Experience working in cross-functional teams and agile environments.
 
 
 </li>
 </ul>
 
 2&ndash; Technical Skills
 
 
 
 <ul>
 <li>
 Strong SQL and advanced data modeling techniques
 </li>
 <li>
 Apache Spark (PySpark, Spark SQL, Streaming)
 </li>
 <li>
 Python (pandas, PySpark, data processing libraries)
 </li>
 <li>
 Data pipeline orchestration (Apache Airflow)
 </li>
 <li>
 CI/CD for data pipelines (GitHub Actions / Azure DevOps)
 </li>
 <li>
 Lakehouse architectures (Delta Lake / Iceberg / Hudi)
 </li>
 <li>
 Streaming technologies (Kafka, Flink)
 </li>
 <li>
 Cloud platforms (AWS / Azure / GCP)
 </li>
 <li>
 Vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
 </li>
 <li>
 RAG pipeline design and LLM data processing
 </li>
 <li>
 Infrastructure-as-Code (Terraform / Bicep / CDK)
 </li>
 <li>
 Containers (Docker, Kubernetes)
 </li>
 <li>
 Data quality &amp; governance tools
 </li>
 </ul>
</div>

Senior AI Data Engineer

Koinz

<div>
 
 About Koinz:
 
 
 
 Koinz is a fast-growing social ecommerce mobile app specializing in food ordering and innovative loyalty programs across the MENA region, notably in Saudi Arabia and Egypt. We're dedicated to enhancing our users&rsquo; experiences through seamless, engaging, and rewarding interactions.
 
 
 
 Role brief:
 
 
 
 We are seeking a highly skilled and motivated Senior Data Engineer to join our dynamic and growing team. You will be instrumental in designing, developing, and optimizing our next-generation data infrastructure, driving key business insights.
 
 
 
 What You'll Bring:
 
 
 
 <ul>
 <li>
 3+ years of professional experience in data engineering or a related field
 </li>
 <li>
 Proficiency in developing data processing jobs using Apache Spark
 </li>
 <li>
 Experience with workflow orchestration tools, specifically Apache Airflow, including designing and maintaining complex DAGs
 </li>
 <li>
 Strong programming skills in Python (including data-related libraries like Pandas, NumPy) for scripting, automation, and ETL/ELT development
 </li>
 <li>
 Mastery of SQL for complex querying, data modeling, and performance tuning in various relational databases
 </li>
 <li>
 Solid understanding of data warehousing concepts, ETL/ELT principles, and dimensional modeling
 </li>
 <li>
 Excellent problem-solving skills and the ability to work independently and as part of a team
 
 
 </li>
 </ul>
 
 Key Responsibilities:
 
 
 
 <ul>
 <li>
 Design, build, and maintain efficient, scalable, and reliable data pipelines using Spark, Python, and Airflow
 </li>
 <li>
 Develop optimal SQL queries and stored procedures to ensure data quality and integrity
 </li>
 <li>
 Collaborate with data analysts to understand data needs and deliver data sets that power business decisions and machine learning models
 </li>
 <li>
 Implement robust monitoring, alerting, and logging for all data pipelines to ensure high operational stability
 </li>
 <li>
 Optimize data architecture for performance, cost-efficiency, and security
 
 
 </li>
 </ul>
 Powered by JazzHR
 
 
 PJ7GmyHdvJ
</div>

Senior Data Engineer

Sana Commerce

<div>
 
 What started in 2007 with a pizza and a plan has grown into a fast-moving SaaS company empowering manufacturers, distributors, and wholesalers to thrive in complex B2B commerce.
 
 
 
 
 Our mission is simple: help businesses build stronger relationships through seamless digital commerce.
 
 
 
 
 At Sana Commerce, we're looking for a
 
 Data Engineer (ML/AI)
 
 to design, build, and scale data systems that power our analytics and machine learning initiatives. Your work will ensure high-quality, reliable, and ML-ready data pipelines that enable both traditional analytics and advanced AI-driven solutions across the business.
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 What you'll be doing
 
 
 
 
 <ul>
 <li>
 Designing and maintaining
 
 data pipelines optimized for ML/AI workloads
 
 , including handling of large-scale, unstructured, and semi-structured data.
 </li>
 <li>
 Building
 
 feature pipelines and feature stores
 
 that ensure reusability and consistency of data used by machine learning models.
 </li>
 <li>
 Collaborating with Data Scientists and ML Engineers to understand
 
 data requirements for training, validation, and production deployment
 
 .
 </li>
 <li>
 Ensuring
 
 data quality, lineage, and governance
 
 meet standards required for AI/ML applications.
 </li>
 <li>
 Supporting
 
 MLOps practices
 
 by integrating data pipelines with model training, monitoring, and deployment workflows.
 </li>
 <li>
 Leveraging distributed processing frameworks (e.g., Spark, Databricks, Azure Synapse) for
 
 scalable ML data processing
 
 .
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 What you bring
 
 
 
 
 <ul>
 <li>
 
 8+ years
 
 of experience as a Data Engineer, working with Azure and Databricks, ideally with exposure to
 
 ML/AI-related data workflows
 
 .
 </li>
 <li>
 College degree that demonstrates your analytic abilities, such as Econometrics, Computer Sciences, Mathematics or similar;
 </li>
 <li>
 Excellent analytical and problem-solving skills;
 </li>
 <li>
 Experience with
 
 data preparation for ML/AI
 
 : managing large datasets, feature engineering, and real-time or batch data pipelines.
 </li>
 <li>
 Familiarity with
 
 MLOps concepts
 
 and how data engineering supports model lifecycle management.
 </li>
 <li>
 Experience with orchestration frameworks (Airflow, Prefect, or Azure Data Factory) for
 
 complex ML pipelines
 
 .
 </li>
 <li>
 Knowledge of unstructured data processing (text, images, logs) is a plus.
 </li>
 <li>
 Strong SQL and Python skills; experience with distributed data processing (PySpark, Dask, etc.) is a plus.
 </li>
 </ul>
 
 
 Why you&rsquo;ll love working here
 
 
 
 
 <ul>
 <li>
 Impact from day one &ndash; Join a scale-up where your ideas shape how global businesses operate online.
 </li>
 <li>
 Continuous learning &ndash; Access a structured onboarding rated 9.1/10 by previous hires, mentorship, and feedback culture.
 </li>
 <li>
 Hybrid flexibility &ndash; Work from our office in Alexandria 3 days per week and from home 2 days.
 </li>
 <li>
 Career growth &ndash; Expand your technical and leadership scope in a company built for long-term success.
 </li>
 </ul>
 
 
 Our values
 
 
 
 
 
 At Sana Commerce, our values drive everything we do:
 
 
 
 <ul>
 <li>
 Champions of Our League &ndash;
 
 We deliver lasting success, balancing quick wins and long-term value
 
 </li>
 <li>
 Supercharge Our Customers &ndash;
 
 We&rsquo;re revolutionizing B2B commerce together, helping our customers to lead and succeed.
 
 </li>
 <li>
 Determined to Grow &ndash;
 
 We embrace challenges, growing and raising the bar for ourselves and our industry.
 
 </li>
 <li>
 Bold Together &ndash;
 
 We dare to be bold because we have each other&rsquo;s back.
 
 </li>
 </ul>
 
 
 Ready to build reliability that scales?
 
 
 
 
 
 Apply now and help shape the foundation of our next-generation SaaS platform.
 
 
 
 
 
 
 Additional Information
 
 
 
 
 
 
 
 
 
</div>

Senior Data Engineer (ML/AI) - Alexandria

Infomineo

<div>
 
 Description
 
 
 
 About us:
 
 
 
 Infomineo is a fast-growing business insights provider, bringing Brainshoring to global clients across a range of services: Business research, Content Services, Graphic Design, and Data Analytics. Our clients include leading Consultancies, Fortune 500 companies, Governments, and NGOs. Infomineo counts 350+ employees spread across 5 offices covering EMEA and the Americas (Casablanca, Cairo, Dubai, Barcelona and Mexico City).
 
 
 
 About this role:
 
 
 
 We are actively seeking a highly skilled and experienced individual to join us as a Senior Research &amp; Development Engineer. This role requires expertise in DevOps, Cloud Computing, AI projects, API integration, and preferably data engineering. The ideal candidate will play a pivotal role in defining and developing initiatives that leverage AI and automation technologies to enhance our products and services.
 
 
 
 
 
 Key Responsibilities:
 
 <ul>
 <li>
 Technical Development and Automation:
 </li>
 <li>
 Lead the development and implementation of AI-driven solutions, focusing on automation and efficiency.
 </li>
 <li>
 Utilize DevOps principles to streamline development processes and ensure seamless deployment of AI applications.
 </li>
 <li>
 Collaborate with cross-functional teams to integrate AI capabilities into existing systems.
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Cloud Architecture and Integration:
 </li>
 <li>
 Design and implement scalable cloud architectures to support AI initiatives.
 </li>
 <li>
 Integrate AI solutions with cloud platforms, ensuring optimal performance and scalability.
 </li>
 <li>
 Implement best practices for cloud security and compliance.
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 API Integration and Data Engineering:
 </li>
 <li>
 Develop and maintain API integrations to enhance data flow between different systems.
 </li>
 <li>
 Leverage data engineering techniques to process and analyze large datasets for AI model training.
 </li>
 <li>
 Ensure data quality and integrity throughout the integration process.
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 AI Project Management:
 </li>
 <li>
 Utilize agile methodologies to manage the lifecycle of AI development projects.
 </li>
 <li>
 Collaborate with stakeholders to define project requirements and deliverables.
 </li>
 <li>
 Track and report on project progress, addressing any challenges or bottlenecks.
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 Continuous Improvement and Innovation:
 </li>
 <li>
 Stay updated on the latest advancements in AI, automation, and related technologies.
 </li>
 <li>
 Propose and implement improvements to existing systems and processes.
 </li>
 <li>
 Foster a culture of innovation within the team, encouraging creative problem-solving.
 </li>
 </ul>
 
 
 
 
 Qualifications:
 
 <ul>
 <li>
 3 to 5 years Proven experience in DevOps, Cloud Computing, AI projects and API integration.
 </li>
 <li>
 In-depth knowledge of cloud platforms (e.g., AWS, Azure, GCP).
 </li>
 <li>
 Experience with containerization technologies (e.g., Docker, Kubernetes).
 </li>
 <li>
 Solid understanding of data engineering principles and practices.
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Technology, or a related field.
 </li>
 </ul>
 
 
 
 
 Preferred Skills:
 
 <ul>
 <li>
 Certifications in relevant technologies (e.g., AWS Certified DevOps Engineer, TensorFlow Developer).
 </li>
 <li>
 Previous experience in data engineering
 </li>
 <li>
 Strong proficiency in relevant programming languages (e.g., Python, Java).
 </li>
 <li>
 Previous experience in developing and deploying AI models in a production environment.
 </li>
 <li>
 Familiarity with machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in building and maintaining data pipelines.
 </li>
 </ul>
 
 What We Offer:
 
 <ul>
 <li>
 Competitive salary and benefits.
 </li>
 <li>
 Opportunity to shape and drive AI and automation initiatives.
 </li>
 <li>
 A collaborative and forward-thinking work environment.
 </li>
 <li>
 Professional development and career growth opportunities.
 </li>
 </ul>
 
 
 
 
 Application Process:
 
 
 Candidates are invited to submit a resume, cover letter, and any relevant portfolio or GitHub links showcasing their experience in DevOps, Cloud Computing, AI projects, API integration, and data engineering. Shortlisted candidates may undergo a technical assessment or interview process to demonstrate their skills.
 
 
 
 
 
 
 What is it like to work at Infomineo?
 
 
 
 If you've spoken with someone who works at Infomineo, you've probably heard that our people are our most valuable asset. Our diversity, both in terms of professional experience and culture, is the company&rsquo;s greatest strength. By being a part of Infomineo, you'll have the opportunity to work alongside a friendly, smart, and international team of researchers that value intellectual vitality and creativity. You will learn the best practices, tools to use when conducting primary and secondary research. You will grow your career, expertise across different regions and industries. As a member of the team, you'll be encouraged to contribute by applying your ideas while playing an instrumental role in the company&rsquo;s development and growth. Within this role, you'll support leading international institutions &amp; companies with the data and information required to fuel key business decisions.
 
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