h3Job Description /h3 pAre you passionate about the intersection of Artificial Intelligence, Machine Learning, and robust software development practices? Do you have a foundational understanding of DevOps principles and a keen interest in applying them to AI solutions? We are looking for an Associate DevOps Engineer to join our team and contribute to developing, deploying, and maintaining AI-powered tools that streamline and enhance the daily workflows of our RD engineers across hardware, software, architecture, and test functions. /p pIn this role, you will work closely with experienced engineers, learning to bridge the gap between AI development and operational excellence. You will help ensure our RD teams can leverage AI tools safely, effectively, and efficiently, gaining valuable hands‑on experience in a supportive environment. /p h3How You Will Contribute And What You Will Learn /h3 h3Support AI Solution Development Integration: /h3 ul liAssist in the development and integration of AI-driven tools and platforms (e.g., internal LLM chatbots, specialized applications) into existing RD workflows and systems. /li liCollaborate with AI experts and RD engineers to understand their needs and contribute to building effective AI solutions. /li liLearn about and contribute to use cases such as initial code drafting, test scaffolding, refactoring, documentation generation, test plan generation, script generation, log analysis, debugging, and design option exploration. /li /ul h3Contribute to DevOps Pipelines for AI: /h3 ul liSupport the building, maintenance, and optimization of CI/CD pipelines for AI models and applications, focusing on automated testing, deployment, and continuous integration. /li liGain hands‑on experience with tools like GitLab, Artifactory, Argo CD, and SonarQube for efficient and secure software delivery. /li liLearn and apply DevSecOps practices to embed security throughout the AI solution lifecycle. /li /ul h3Assist with Infrastructure Cloud Management: /h3 ul liHelp manage and provision cloud infrastructure (e.g., Azure, NESC, AWS) using Infrastructure as Code (IaC) principles with tools like Terraform and Kubernetes. /li liSupport the configuration and access for approved AI tools and environments, adhering to corporate policies and security baselines. /li liAssist in the deployment and lifecycle management of containerized AI applications. /li /ul h3Monitor, Log Optimize Performance:

/h3 ul liContribute to implementing monitoring and logging solutions (e.g., Prometheus, Grafana, ELK stack) for AI tools and their underlying infrastructure. /li liLearn to identify and help resolve performance bottlenecks, ensuring the reliability of AI services. /li liParticipate in the continuous improvement of AI-assisted RD processes by analyzing metrics and feedback. /li /ul h3Develop AI/ML Understanding Application: /h3 ul liApply academic knowledge or project experience in machine learning fundamentals, algorithms (e.g., Linear Regression, Neural Networks, Deep Learning), and data science techniques. /li liDevelop skills in prompt engineering to maximize the effectiveness of large language models for RD tasks. /li liUnderstand basic data preprocessing, feature selection, model evaluation, and deployment strategies in cloud and local environments. /li /ul h3Collaborate Communicate: /h3 ul liWork effectively within RD teams, learning from architects, product owners, and the PSE AI Council to align AI initiatives with business objectives and technical standards. /li liProvide support to RD engineers on the effective and safe use of AI tools. /li liLearn about and report suspected policy violations or data leakage related to AI usage through established channels. /li /ul h3Key Skills And Experience /h3 ul liBachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical field (or graduating soon). /li liAcademic projects, internships, or demonstrable personal projects showcasing an understanding of DevOps principles and practices. /li liFoundational knowledge of AI/ML concepts, including basic model development or application. /li liFamiliarity with at least one scripting language (e.g., Python, Bash) and an eagerness to learn relevant AI/ML libraries. /li liBasic understanding of cloud platforms (e.g., Azure, AWS, OpenStack) and containerization (e.g., Docker, Kubernetes). /li liAwareness of IaC concepts (e.g., Terraform, Ansible).

/li liBasic understanding of monitoring and logging tools (e.g., Prometheus, Grafana, ELK). /li liInterest in secure coding practices and DevSecOps principles. /li liStrong problem-solving aptitude, analytical skills, and clear communication. /li liEagerness to learn and adapt in an agile, fast-paced RD environment. /li /ul h3About Us /h3 pAdvancing connectivity to secure a brighter world. /p pNokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world. /p pLearn more about life at Nokia . /p h3Our recruitment process /h3 pWe act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect. /p pIf you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity. /p pThe length of the recruitment process may vary depending on the specific role’s requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia . /p h3About The Team /h3 pSome of our benefits: /p ul liFlexible and hybrid working schemes /li liA minimum of 90 days of Maternity and Paternity Leave, with the option to return to work within a year following the birth or adoption of a child (based on eligibility) /li liLife insurance to all employees to provide peace of mind and financial security /li liWell-being programs to support your mental and physical health /li liOpportunities to join and receive support from Nokia Employee Resource Groups (NERGs) /li liEmployee Growth Solutions to support your personalized career skills development /li liDiverse pool of Coaches Mentors to whom you have easy access /li liA learning environment which promotes personal growth and professional development - for your role and beyond /li /ul #J-18808-Ljbffr

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