senior data engineer

senior network engineer

ai platform engineer

senior software engineer

software engineer

ai genai solutions engineer

Soum

<div>
 
 Role Name: AI / GenAI Solutions Engineer
 
 
 
 Location:
 
 Egypt, Saudi Arabia, and Pakistan (Remote)
 
 
 
 Work Week:
 
 Sunday - Thursday
 
 
 
 Working Hours:
 
 9:00 AM - 6:00 PM (Saudi Arabia Standard Time)
 
 
 
 Overview:
 
 
 Soum is on a mission to revolutionize customer service experiences across our C2C marketplace through cutting-edge AI solutions. We&rsquo;re looking for a talented
 
 AI / GenAI Solutions Engineer
 
 who will architect, build, and deploy intelligent systems that transform how we engage with millions of users.
 
 
 You&rsquo;ll be at the forefront of GenAI innovation&mdash;leveraging tools like Gemini Advanced, Claude Enterprise, and ChatGPT&mdash;to design scalable, reliable, and context-aware AI agents deeply integrated into Soum&rsquo;s ecosystem. This is your chance to make a tangible impact on how customers interact with our platform while working in a collaborative, fast-paced environment.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Build GenAI-powered solutions: Design, develop, and deploy scalable business workflows using GenAI client tools (e.g., Gemini Advanced, NotebookLM, Claude Enterprise) and integrate them with existing systems via APIs (Freshdesk, Google Workspace, Airtable, etc.)
 </li>
 <li>
 Drive AI innovation: Evaluate and experiment with emerging GenAI technologies, stay ahead of industry trends, and pilot innovative solutions tailored for Soum&rsquo;s marketplace
 </li>
 <li>
 Ensure scalability and reliability: Architect solutions that can handle high-volume, concurrent user interactions while maintaining low latency and excellent user experience
 </li>
 <li>
 Partner cross-functionally: Collaborate with Product, Data, Engineering, and Customer Support teams to identify opportunities for automation and deliver impactful, user-centric solutions
 </li>
 <li>
 Evangelize AI adoption: Share best practices, contribute to technical knowledge-sharing sessions, and promote a culture of continuous improvement and innovation
 </li>
 <li>
 Bridge technical gaps: Integrate custom-built AI platforms with out-of-the-box GenAI tools, fostering democratization and ease of adoption across teams
 
 
 
 
 
 </li>
 </ul>
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree, preferably in Computer Science, Engineering, or a related technical field
 </li>
 <li>
 3+ years of relevant experience in AI or related fields
 </li>
 <li>
 Experience designing, building, and deploying AI/ML systems at scale in conversational AI contexts
 </li>
 <li>
 Deep hands-on experience using and implementing GenAI tools (e.g., Gemini, ChatGPT, Claude Enterprise) to solve real-world business problems
 </li>
 <li>
 Strong understanding of SaaS ecosystems, API integrations (including Google Workspace, Airtable, Freshdesk)
 </li>
 <li>
 Expertise in NLP/NLU, conversational AI frameworks, and large language models
 </li>
 <li>
 Proficiency in Python and JavaScript for scripting, automation, and lightweight prototyping
 </li>
 <li>
 Practical experience integrating AI solutions into production systems via APIs, microservices, and event-driven architectures
 </li>
 <li>
 Experience working on a C2C platform. Solid understanding of marketplace dynamics, customer support challenges, and user engagement in a C2C environment
 </li>
 <li>
 Experience implementing conversational flows, dialogue management, and context tracking in AI agents
 </li>
 <li>
 Familiarity with retrieval-augmented generation (RAG) architectures for enhancing LLM capabilities
 </li>
 <li>
 Understanding of data privacy, security, and ethical considerations in AI deployments
 </li>
 <li>
 Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively
 
 
 
 
 
 </li>
 </ul>
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>

AI / GenAI Solutions Engineer

Intellias

<div>
 
 
 MLOps Engineer
 
 
 
 We have a dream: to change industries through the power of digital technology. At Intellias, you will work with top-tier engineers to build and deploy cutting-edge machine learning solutions that bring AI models into real-world production at scale.
 
 
 You will join a dynamic team focused on designing and maintaining robust MLOps infrastructure for deploying and managing ML/AI systems across cloud environments, enabling the next generation of intelligent products.
 
 
 
 Requirements
 
 
 <ul>
 <li>
 5+ years of experience in
 
 MLOps, ML engineering, or similar roles
 
 </li>
 <li>
 Master&rsquo;s or higher degree in Computer Science or related field
 </li>
 <li>
 Strong experience in
 
 Computer Vision, NLP, or Generative AI
 
 </li>
 <li>
 Advanced programming skills in
 
 Python or Rust
 
 </li>
 <li>
 Experience building
 
 scalable ML pipelines
 
 (training, validation, deployment)
 </li>
 <li>
 Hands-on experience with
 
 AWS / Azure / GCP
 
 </li>
 <li>
 Experience with
 
 Kubernetes, Docker, and CI/CD
 
 </li>
 <li>
 Knowledge of
 
 Kubeflow, Airflow, Argo, or similar orchestration tools
 
 </li>
 <li>
 Experience with
 
 model registries and feature stores
 
 </li>
 <li>
 Experience deploying DL models using
 
 PyTorch or TensorFlow
 
 </li>
 <li>
 Experience building
 
 REST APIs (FastAPI or similar)
 
 </li>
 <li>
 Experience with
 
 GenAI agents (LangChain or similar)
 
 and LLM evaluation/observability
 </li>
 <li>
 Knowledge of
 
 Infrastructure as Code (Terraform)
 
 </li>
 <li>
 Strong communication and collaboration skills
 </li>
 </ul>
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience deploying LLMs on-prem
 </li>
 <li>
 GCP ML Engineer certification
 </li>
 <li>
 Industry experience in retail, finance, healthcare, telecom, energy, or manufacturing
 </li>
 <li>
 Experience with data science projects
 </li>
 </ul>
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Lead and support technical POCs and ML projects
 </li>
 <li>
 Design and improve MLOps architectures following best practices
 </li>
 <li>
 Support discovery phases and technical consulting
 </li>
 <li>
 Collaborate on presales and upsales activities
 </li>
 <li>
 Contribute to knowledge sharing and public speaking initiatives
 </li>
 </ul>
 
 
 Why Join Us
 
 
 
 At Intellias, people come first. We foster a culture where innovation thrives, enabling engineers to work on impactful AI solutions while continuously growing their expertise in a supportive and forward-thinking environment.
 
</div>

Machine Learning Ops 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.
 
 
 
 Our mission is to revolutionize existing and new Valeo products, tools and processes by harnessing the power of cutting-edge generative AI. We aim to drive unprecedented efficiency across Valeo product portfolio, reducing development costs and achieving a new level of intelligent automation.
 
 
 
 
 Through relentless research, we design and build a robust and adaptable AI framework that seamlessly integrates into our current workflow.
 
 
 
 
 We are committed to fostering a collaborative environment where researchers, engineers, and product teams work in unison to explore innovative solutions. We believe that by strategically integrating AI, we can optimize internal processes, streamline workflows, and drive long-term success within Valeo's existing and new product landscape.
 
 
 
 
 Responsibilities
 
 
 
 
 This position is the cornerstone of the AI4ALL team, he is responsible for developing applications, testing and maintaining them.
 
 
 
 <ul>
 <li>
 Develop &amp; re-use the core AI components of the framework.
 </li>
 <li>
 Implement APIs, models, optimize for performance, and integrate with adjacent systems.
 </li>
 <li>
 Conduct various testing (Unit Test, API Testing, Load Testing, &hellip;) for the developed components.
 </li>
 <li>
 Document all the developed components.
 </li>
 <li>
 Deploy developed products and maintain them.
 </li>
 <li>
 Build user-facing product features using the framework's capabilities
 </li>
 <li>
 Create responsive UI components, ensure smooth interactions with AI models
 </li>
 <li>
 Manage client-side data handling
 </li>
 <li>
 Conduct various frontend testing
 
 
 </li>
 </ul>
 
 
 Education/Training
 
 
 
 
 <ul>
 <li>
 B.Sc. in Communication, Mechatronics, Electronics or Computer Engineering.
 </li>
 <li>
 B.Sc. in Computer science
 
 
 </li>
 </ul>
 
 
 Professional Competences
 
 
 
 
 
 Deep learning (TensorFlow, PyTorch)
 
 
 2
 
 
 
 
 Collaborative mindset
 
 
 3
 
 
 
 
 Knowledge of GenAI Framework (LangChain, LlamaIndex)
 
 
 3
 
 
 
 
 Focus on code quality
 
 
 3
 
 
 
 
 Strong knowledge of OOP &amp; Functional Programming
 
 
 3
 
 
 
 
 Self-organized
 
 
 3
 
 
 
 
 Python, REST API development
 
 
 3
 
 
 
 
 Experience with Python based web framework (Flask, FastAPI, Django)
 
 
 3
 
 
 
 
 JavaScript/TypeScript, HTML, CSS
 
 
 3
 
 
 
 
 Frontend Frameworks at least one (React, Vue, Angular)
 
 
 2
 
 
 
 
 Experience with Python based test framework (PyTest, PyUnit)
 
 
 2
 
 
 
 
 Knowledge of Cloud Services (GCP, AWS)
 
 
 2
 
 
 
 
 
 Professional
 
 
 Experience
 
 
 
 
 <ul>
 <li>
 3+ Years of experience.
 </li>
 <li>
 Knowledge of AI/ML and GenAI.
 </li>
 <li>
 Knowledge of at least one Web framework (FastAPI, Django, Flask, &hellip;).
 </li>
 <li>
 Knowledge of (HTML, CSS, JS)
 </li>
 <li>
 Knowledge of React frontend framework is a plus.
 </li>
 <li>
 Knowledge and development for cloud platforms (GCP, AWS) is a plus.
 
 
 </li>
 </ul>
 
 
 Other Specifications
 
 
 
 
 
 We prefer a great/interested/excited team player with less experience to an unmotivated or unengaged one with tons of experience.
 
 
 
 
 Position~
 
 
 
 R&amp;D IS Engineer
 
 
 
 D&eacute;partement~
 
 
 
 Software Development
 
 
 
 Schedule~
 
 
 
 Temps plein
 
 
 
 Employee Status~
 
 
 
 CDI
 
 
 
 Type de contrat~
 
 
 
 
 Job Posting Date~
 
 
 
 2026-01-26
 
 
 
 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 Full Stack Developer, AI4ALL

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

<div>
 
 Our mission is to revolutionize existing and new Valeo products, tools and processes by harnessing the power of cutting-edge generative AI. We aim to drive unprecedented efficiency across Valeo product portfolio, reducing development costs and achieving a new level of intelligent automation.
 
 
 
 
 Through relentless research, we design and build a robust and adaptable AI framework that seamlessly integrates into our current workflow.
 
 
 
 
 We are committed to fostering a collaborative environment where researchers, engineers, and product teams work in unison to explore innovative solutions. We believe that by strategically integrating AI, we can optimize internal processes, streamline workflows, and drive long-term success within Valeo's existing and new product landscape.
 
 
 
 
 Responsibilities
 
 
 
 
 This position is the cornerstone of the AI4ALL team, he is responsible for developing applications, testing and maintaining them.
 
 
 
 <ul>
 <li>
 Develop &amp; re-use the core AI components of the framework.
 </li>
 <li>
 Implement APIs, models, optimize for performance, and integrate with adjacent systems.
 </li>
 <li>
 Conduct various testing (Unit Test, API Testing, Load Testing, &hellip;) for the developed components.
 </li>
 <li>
 Document all the developed components.
 </li>
 <li>
 Deploy developed products and maintain them.
 </li>
 <li>
 Build user-facing product features using the framework's capabilities
 </li>
 <li>
 Create responsive UI components, ensure smooth interactions with AI models
 </li>
 <li>
 Manage client-side data handling
 </li>
 <li>
 Conduct various frontend testing
 
 
 </li>
 </ul>
 
 
 Education/Training
 
 
 
 
 <ul>
 <li>
 B.Sc. in Communication, Mechatronics, Electronics or Computer Engineering.
 </li>
 <li>
 B.Sc. in Computer science
 
 
 </li>
 </ul>
 
 
 Professional Competences
 
 
 
 
 
 Deep learning (TensorFlow, PyTorch)
 
 
 2
 
 
 
 
 Collaborative mindset
 
 
 3
 
 
 
 
 Knowledge of GenAI Framework (LangChain, LlamaIndex)
 
 
 3
 
 
 
 
 Focus on code quality
 
 
 3
 
 
 
 
 Strong knowledge of OOP &amp; Functional Programming
 
 
 3
 
 
 
 
 Self-organized
 
 
 3
 
 
 
 
 Python, REST API development
 
 
 3
 
 
 
 
 Experience with Python based web framework (Flask, FastAPI, Django)
 
 
 3
 
 
 
 
 JavaScript/TypeScript, HTML, CSS
 
 
 3
 
 
 
 
 Frontend Frameworks at least one (React, Vue, Angular)
 
 
 2
 
 
 
 
 Experience with Python based test framework (PyTest, PyUnit)
 
 
 2
 
 
 
 
 Knowledge of Cloud Services (GCP, AWS)
 
 
 2
 
 
 
 
 
 Professional
 
 
 Experience
 
 
 
 
 <ul>
 <li>
 3+ Years of experience.
 </li>
 <li>
 Knowledge of AI/ML and GenAI.
 </li>
 <li>
 Knowledge of at least one Web framework (FastAPI, Django, Flask, &hellip;).
 </li>
 <li>
 Knowledge of (HTML, CSS, JS)
 </li>
 <li>
 Knowledge of React frontend framework is a plus.
 </li>
 <li>
 Knowledge and development for cloud platforms (GCP, AWS) is a plus.
 
 
 </li>
 </ul>
 
 
 Other Specifications
 
 
 
 
 
 We prefer a great/interested/excited team player with less experience to an unmotivated or unengaged one with tons of experience.
 
</div>

Siemens

<div>
 
 About Brightly Software
 
 
 
 Brightly Software is a leader in intelligent asset management and operational optimization, empowering organizations with data‑driven insights. As we expand our AI and ML capabilities, we are seeking a Senior MLOps Engineer to build and scale the infrastructure that powers our next generation of predictive and autonomous solutions.
 
 
 
 Role Overview
 
 
 
 As a Senior MLOps Engineer, you will architect, develop, and operate end‑to‑end machine learning infrastructure on AWS. You will work at the intersection of ML engineering, cloud infrastructure, and developer productivity&mdash;enabling Brightly's data science teams to move seamlessly from experimentation to reliable, secure, and cost‑efficient production systems.
 
 
 Your work will ensure that ML models and data pipelines are scalable, observable, and compliant with best‑in‑class MLOps practices.
 
 
 
 Key Responsibilities
 
 
 
 
 ML Platform &amp; Infrastructure (AWS‑focused)
 
 
 
 <ul>
 <li>
 Design, build, and operate ML/AI development platforms on AWS, leveraging services such as Amazon SageMaker (Studio, Training, Real‑Time &amp; Async Inference, Pipelines, Feature Store), S3, Glue, Lambda, ECS/EKS, and related cloud infrastructure.
 </li>
 <li>
 Implement infrastructure‑as‑code using Terraform or equivalent, and manage workflow orchestration using AWS Step Functions or Airflow.
 
 
 </li>
 </ul>
 
 Data &amp; Model Pipelines
 
 
 
 <ul>
 <li>
 Build automated data ingestion and transformation pipelines using S3, Glue, EMR/Spark, and Redshift, incorporating data quality and lineage tooling (e.g., Great Expectations, Deequ).
 
 
 </li>
 </ul>
 
 CI/CD for Machine Learning
 
 
 
 <ul>
 <li>
 Develop CI/CD pipelines for ML with CodeBuild, CodePipeline, or GitHub Actions, integrating unit tests, data contract checks, model validation, canary/shadow deployments, and automated rollback strategies.
 
 
 </li>
 </ul>
 
 Model Deployment &amp; Operations
 
 
 
 <ul>
 <li>
 Deploy real‑time inference endpoints (SageMaker endpoints or FastAPI‑based services on Lambda/ECS/EKS) and scalable batch processing jobs.
 </li>
 <li>
 Define SLOs, implement autoscaling, and drive cost/performance optimizations across ML workloads.
 
 
 </li>
 </ul>
 
 Monitoring, Observability &amp; Governance
 
 
 
 <ul>
 <li>
 Implement production monitoring for drift, bias, and performance using SageMaker Model Monitor and service telemetry tools like CloudWatch, Prometheus, and Grafana.
 </li>
 <li>
 Enforce security and governance best practices, including least‑privilege IAM, VPC‑isolated architectures, encryption, and secret management.
 
 
 </li>
 </ul>
 
 Cross‑Functional Collaboration
 
 
 
 <ul>
 <li>
 Partner closely with data scientists, ML engineers, and backend engineers to productionize ML models and streamline development workflows.
 </li>
 <li>
 Contribute to the integration of emerging GenAI workloads, including Amazon Bedrock, vector databases (e.g., OpenSearch), and RAG pipelines.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related field.
 </li>
 <li>
 7+ years of professional experience in ML engineering, DevOps, cloud engineering, or MLOps roles, with at least 3 years in a senior or lead capacity.
 </li>
 <li>
 3+ years of proven track record in designing and architecting robust, scalable ML systems and infrastructure in cloud environments, particularly on AWS.
 </li>
 <li>
 5+ years of deep experience building on the AWS ML ecosystem, including SageMaker, S3, Lambda, ECR, EKS/ECS, Step Functions, IAM, VPC networking, and CI/CD tooling.
 </li>
 <li>
 3+ years of hands-on experience deploying, maintaining, and scaling ML models in production environments.
 </li>
 <li>
 3+ years of strong Python development skills and familiarity with Docker‑based workflows.
 </li>
 <li>
 5+ years of solid understanding of ML lifecycles, model evaluation, and monitoring patterns.
 </li>
 <li>
 5+ years of extensive experience with infrastructure‑as‑code (Terraform, CloudFormation).
 </li>
 <li>
 5+ years of expertise in designing system architecture for ML platforms, including microservices, container orchestration, and cloud networking.
 </li>
 <li>
 3+ years of familiarity with MLOps best practices as defined by AWS and industry standards.
 </li>
 <li>
 2+ years of experience with data quality frameworks (Great Expectations, Deequ).
 </li>
 <li>
 2+ years of experience optimizing distributed training workflows on AWS.
 </li>
 <li>
 3+ years of knowledge of security and compliance requirements for ML in enterprise settings, such as IAM, encryption, and secret management.
 </li>
 <li>
 2+ years of experience with monitoring tools (CloudWatch, Prometheus, Grafana) and implementing model observability solutions.
 </li>
 <li>
 5+ years of effective cross-functional collaboration skills, working closely with data scientists, ML engineers, and software engineers to deliver production-grade ML solutions.
 </li>
 <li>
 7+ years of excellent problem-solving and communication abilities, with a focus on delivering scalable, reliable, and cost-effective ML platforms.
 
 
 </li>
 </ul>
 
 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>

Senior Machine Learning Operations Engineer

Coca-Cola HBC

<div>
 
 
 Department:
 
 Data, Insights &amp; Artificial Intelligence (DIAI)
 
 
 
 Location:
 
 Egypt, Bulgaria, Greece
 
 
 
 
 
 As a Product Expert for Data Control &amp; Data Quality, you will play a key role in the design, build, configuration, monitoring and continuous improvement of Coca-Cola Hellenic&rsquo;s Data Quality Management products, with a primary focus on the Data Control Center (DCC). You will work closely with the Data Quality &amp; Standards Product Manager, Business Stakeholders, Business Unit Data Stewards and IT partners (DTPS), ensuring that data quality controls, monitoring and reporting enable reliable and trusted data across the organization. This is a hands-on data engineering role requiring strong technical skills in SQL, PySpark and Azure-based data platforms and the emerging AI and GenAI techniques, combined with full ownership of deliverables from production support and the flexibility to handle ad-hoc requests and parallel priorities while translating business requirements into scalable, automated and intelligent data quality solutions.
 
 
 
 
 
 
 YOUR NEW KEY RESPONSIBILITIES
 
 
 
 
 Data Quality Controls (DCC)
 
 
 
 &bull; Lead the design and end-to-end ownership of Data Quality controls in the Data Control Center (DCC), from implementation through production support and continuous improvement
 
 
 &bull; Translate business requirements into data quality rules, including logic definition, thresholds, exception handling and reduction of false positives
 
 
 &bull; Discover the possibility of AI solutions for advanced checks and/or smart data errors remediation.
 
 
 &bull; Ensure DQ controls are aligned with agreed business definitions and standards.
 
 
 
 
 
 
 Monitoring, Operations &amp; Issue Resolution
 
 
 
 &bull; Monitor DQ performance and ensure stable DCC operations, including regular refresh cycles and system reliability.
 
 
 &bull; Troubleshoot failed checks, investigate data issues and perform root-cause analysis in collaboration with relevant stakeholders.
 
 
 &bull; Support incident resolution and contribute to continuous operational improvements.
 
 
 
 
 
 
 Continuous Improvement &amp; Enhancement
 
 
 
 &bull; Implement improvements to existing DQ checks and contribute to the continuous enhancement of DCC capabilities.
 
 
 &bull; Identify opportunities to improve automation, intelligence, scalability and reusability of controls and monitoring processes.
 
 
 &bull; Identify opportunities to automate monitoring and reduce manual effort for stakeholders.
 
 
 
 
 
 
 Reporting &amp; Dashboards
 
 
 
 &bull; Develop and maintain DQ dashboards and scorecards, enabling visibility of DQ KPIs, trends and drilldowns.
 
 
 &bull; Support stakeholders with insights and reporting to track performance and drive quality improvement actions.
 
 
 
 
 
 
 Data Standards Operationalization
 
 
 
 &bull; Support data standards operationalization by ensuring alignment between published standards and DQ checks.
 
 
 &bull; Support adoption and compliance visibility by enabling reporting and transparency on standards adherence.
 
 
 
 
 
 
 Collaboration &amp; Delivery Support
 
 
 
 &bull; Work closely with the Product Manager and business stakeholders to clarify requirements, validate solutions and ensure high usability and adoption.
 
 
 &bull; Collaborate with DTPS and vendors to deliver end-to-end solutions, including integration dependencies and technical enablement.
 
 
 &bull; Run demos and workshops when needed to support rollout, stakeholder understanding and adoption.
 
 
 
 
 
 
 Testing, Release &amp; Documentation
 
 
 
 &bull; Support release and testing activities, including UAT support and regression testing.
 
 
 &bull; Maintain basic documentation of implemented DQ checks, logic, definitions and changes.
 
 
 
 
 
 
 
 
 
 ARE THESE YOUR SECRET INGREDIENTS?
 
 
 
 &bull; 3+ years in data engineering / data science /analytics engineering / data quality engineering
 
 
 &bull; Strong SQL and Python for scalable data validation and monitoring
 
 
 &bull; Experience working with Databricks and modern data pipelines (ADF or similar)
 
 
 &bull; Strong analytical and problem-solving mindset with attention to detail and quality.
 
 
 &bull; Ability to translate business requirements into technical implementation and measurable outcomes.
 
 
 &bull; Comfortable working across multiple stakeholders in a cross-functional environment.
 
 
 &bull; Strong communication skills and ability to explain technical topics to non-technical audiences.
 
 
 &bull; Ownership mindset: proactive, reliable and continuously improving solutions.
 
 
 
 
 
 
 REQUIRED TECHNICAL SKILLS
 
 
 
 &bull; SQL
 
 
 &bull; Python
 
 
 &bull; PySpark
 
 
 &bull; Azure Databricks
 
 
 &bull; Azure Data Factory
 
 
 &bull; Power BI
 
 
 &bull; Machine Learning
 
 
 &bull; AI/ GenAI
 
 
 
 
 
 
 NICE TO HAVE
 
 
 
 &bull; Power Platform (Power Automate, etc.)
 
 
 &bull; Microsoft Fabric
 
 
 &bull; Copilot Studio
 
 
 &bull; Experience working in a Data Mesh framework and/or domain data product mindset
 
 
 &bull; Good awareness of key SAP MDG, MM, S/4HANA domains
 
 
 
 
 
 
 ABOUT YOUR NEW TEAM:
 
 
 
 We are Coca-Cola Hellenic, a growth-focused consumer goods business and strategic bottling partner of the Coca-Cola Company. We bottle, distribute and sell an unrivalled range of products in 29 markets in Europe, Africa and Eurasia. As we do, we create value for all stakeholders, support socio-economic growth and build a more positive environmental impact.
 
 
 We bring together more than 30,000 people from over 70 nationalities, coming from five continents. The diversity of our markets, from mature to emerging economies, provides a wide range of attractive opportunities for growth.
 
 
 We nurture our talents. We give opportunities to people across all functions and levels, as well as different geographies, backgrounds and education. We are willing to take a risk on the people we believe in, even if they don&rsquo;t have the perfect experience. We have faith in what every person can be.
 
 
 And although we have so much to be proud of, we always stay humble. We believe the real magic happens - for us and for you - when we OPEN UP.
 
 
 
 
 
 
 AT COCA-COLA HBC, DIVERSITY HELPS US THRIVE
 
 
 
 At Coca-Cola HBC, we are an inclusive employer that thrives on diversity. This means our environment provides equal opportunities for all, regardless of race, color, religion, age, disability, sexual orientation, or gender identity. Join us in nurturing a culture where everyone belongs and contributes to our collective success.
 
 
 
 
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