• Design, implement, and experiment with machine learning and deep learning models for product use cases • Work on end‑to‑end ML workflows, including: Data preprocessing and feature engineering, Model training, evaluation, and optimization, Experiment tracking and result analysis • Contribute to Generative AI and agentic systems, including: LLM‑based workflows, AI agents, orchestration, and prompt engineering • Develop prototypes and proof‑of‑concepts that can evolve into production features • Write clean, maintainable, and well‑documented Python code • Collaborate with cross‑functional teams (engineering, product, platform) • Present findings, demos, and outcomes to the broader team

Job Title Learning Services Coordinator Job Description The Learning Services Coordinator is responsible for coordinating complex programs, ensuring all logistics are meticulously handled and aligned with customer needs and organizational goals. The role acts as the main contact for high-level inquiries, providing expert guidance and resolving complex issues to maintain high customer satisfaction. The role oversees the entire participant journey, from registration to post-course evaluation, ensuring a seamless experience. The role analyzes and presents training data, contributes to course material development, and manages logistics, including multi-site coordination and technical setup. The role collaborates with cross-functional teams and external partners to enhance the Learning services catalog and executes sophisticated communication strategies to align with organizational priorities. Job Responsibilities: • Coordinates and delivers complex Learning services programs, taking full responsibility for all logistical aspects and ensuring seamless execution aligned with both customer requirements and organizational goals. • Serves as the primary point of contact for high-level inquiries and issues related to Learning services, leveraging deep expertise to provide strategic guidance, resolve complex challenges, and maintain high standards of customer satisfaction. • Exercises autonomy within established procedures, utilizes specialized skills to perform in-depth analysis of assigned tasks, identifying key issues and patterns and resolves moderately complex problems to drive results. • Serves as an informal resource for colleagues with less experience, working on issues where analysis of situation or data requires review of relevant factors and utilizes experience and in-depth knowledge to complete a wide range of tasks in resourceful and effective ways. • Keeps an oversight on the entire participant journey, from initial registration through post-course evaluation, ensuring a high-quality experience by managing communications, addressing special requests, and ensuring all logistical needs are met with precision. • Performs the maintenance, analysis, and presentation of comprehensive training data, generating detailed reports that inform strategic decisions and contribute to continuous improvement in program effectiveness and participant outcomes. • Contributes to the design, development, and continuous improvement of course materials, ensuring they are innovative, meet high educational standards, and are delivered effectively across multiple platforms and formats. • Coordinates all aspects of logistics for complex training programs, including multi-site coordination, advanced technical setup, vendor management, and on-site troubleshooting, ensuring every session is delivered to the highest standard. • Collaborates closely with cross-functional teams, including senior management, project managers, and external partners, to integrate Learning services into broader business initiatives, optimizing resource allocation and ensuring alignment with strategic goals. • Provides input to enhance the Learning services course catalog and departmental tools, leading initiatives to incorporate new technologies and methodologies that improve efficiency and participant engagement. • Executes sophisticated communication strategies, including detailed program plans, executive summaries, and stakeholder updates, ensuring all communications are clear, comprehensive, and aligned with organizational priorities. Minimum 4 years of experience in Learning Services, Training Delivery or equivalent with Vocational Education OR no prior experience with Bachelor's Degree. How we work together We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations. Indicate if this role is an office/field/onsite role. About Philips We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others. • Learn more about our business. • Discover our rich and exciting history. • Learn more about our purpose. If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here.

Join our Team As the Company at the forefront of the creation of the Mobile world, and with more than 60,000 patents to our name, we've made it our business to make a mark. Being part of Ericsson empowers you to learn, lead and perform at your best, shaping future technology. Ericsson is an inclusive employer where you are recognized for the skills, talent, and perspective you bring to the team. Within the Solution Area Cognitive Networks Solutions Software R&D (SA CNS SW R&D), we offer the opportunity to collaborate with highly qualified Global teams and to enable success stories for our customers. You will be exposed to groundbreaking technology (5G, ML/AI, Automation and Cloud computing) and support the delivery of multiple Data-Intensive projects from our customer base and internal requirements. You must have the ability to perform hands-on Cloud and Data engineering tasks independently coupled with the appropriate testing. Are you ready to write the future with us? Come, and be where it begins. About this opportunity: We are seeking an experienced ML/MLOps Lead to guide our cross-functional teams through the complete machine learning lifecycle, from initial prototyping to scalable deployment. You won't just be building models; you will be architecting the ecosystem that sustains them. In this pivotal role, you will bridge the gap between experimental data science and production engineering, establishing technical standards and operational frameworks that turn innovative models into reliable business solutions. If you're passionate about bridging the gap between cutting-edge machine learning and production-scale systems, and thrive in a collaborative environment, we'd love to hear from you. What you will do: - Lead the design and implementation of scalable ML infrastructure and deployment pipelines using AWS SageMaker and other cloud-native ML services - Establish MLOps best practices including model lifecycle management, automated testing, monitoring, and governance frameworks - Architect and implement Infrastructure as Code (IaC) solutions for ML workloads, ensuring reproducibility and scalability - Guide cross-functional teams in translating research prototypes into production-ready ML systems - Drive the adoption of software engineering best practices within ML workflows, including version control, CI/CD, and code quality standards - Mentor team members on ML model optimization, feature engineering, and data pipeline design - Collaborate with stakeholders to define technical requirements and ensure alignment between research initiatives and product delivery - Design and implement monitoring and observability solutions for ML models in production - Lead technical decision-making for ML platform architecture and tooling selection The skills you bring: - 5+ years of experience in machine learning engineering with a strong background in both ML/DS and software engineering - Bachelor's or Master's degree in Computer Science, Data Science, or related field - Proven expertise in MLOps platforms, particularly AWS SageMaker (training, deployment, pipelines, model registry) - Strong proficiency in Infrastructure as Code tools (Terraform, CloudFormation, CDK) - Experience with container technologies (Docker, Kubernetes) and ML orchestration frameworks - Solid programming skills in Python, with experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn) - Deep understanding of CI/CD pipelines, version control (Git), and software development lifecycle - Experience with data engineering tools and practices (ETL/ELT, data versioning, feature stores) - Strong communication and mentoring skills with ability to work across technical and non-technical stakeholders Why join Ericsson? At Ericsson, you'll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what's possible. To build solutions never seen before to some of the world's toughest problems. You'll be challenged, but you won't be alone. You'll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: Egypt (EG) || Cairo Req ID: 775240

• Diseñar, operar y evolucionar nuestra plataforma de AIOps, asegurando que los diferentes productos de inteligencia artificial funcionen de forma fiable, escalable y eficiente. • Trabajar con tecnologías modernas en AWS (Sagemaker), colaborando estrechamente con equipos de data science, ingeniería de datos y producto.