Nokia
Overview
We are seeking a highly skilled AI/ML Domain Architect to design, deploy, and operationalize advanced AI/ML solutions with a focus on MLOps, Generative AI (GenAI), LLM Ops, and Agentic AI integration. This role requires deep expertise in ML engineering practices, cloud-native deployment, and hands-on experience with modern AI platforms. The engineer will be responsible for building scalable ML pipelines, LLM-based applications, and intelligent agent frameworks to accelerate delivery for telecom, enterprise, and next-generation autonomous network solutions. Responsibilities Design, optimize, and scale end-to-end ML pipelines using ML-Ops best practices, including CI/CD, model deployment, and performance monitoring. Develop and operationalize Gen AI/LLM-based solutions, applying techniques such as fine-tuning, prompt engineering, Retrieval-Augmented Generation (RAG), and LLM observability. Integrate Agentic AI frameworks with existing AI/ML systems to enable autonomous decision-making and intelligent workflow orchestration. Implement robust data pipelines for ingestion, preprocessing, and feature engineering across structured, semi-structured, and unstructured data sources. Collaborate cross-functionally with data scientists, solution architects, and delivery teams to translate AI/ML use cases into scalable, production-ready solutions. Design and manage cloud-native AI/ML infrastructure on platforms like Google Cloud (Vertex AI), Red Hat OpenShift AI, and Kubeflow. Deploy scalable AI solutions across multi-cloud and hybrid environments using Kubernetes and container orchestration. Ensure observability and governance of AI systems, including model drift detection, fairness, compliance, and LLM usage guardrails. Create accelerators, reusable frameworks, and automation tools to reduce time-to-market and enhance delivery efficiency. Support customer engagements through proof-of-concepts (PoCs), pilot implementations, and production rollouts.
You Have
Bachelor's/Master's in Computer Science, Data Engineering, AI/ML, or related field. 10+ years of experience in AI/ML engineering, including 5+ years in MLOps. Proven experience with LLM platforms and GenAI ecosystems (OpenAI, Anthropic, Vertex AI, Hugging Face, LangChain, LlamaIndex). Strong proficiency in Python, PyTorch, TensorFlow, Scikit-learn, SQL. Expertise in MLOps pipelines (Kubeflow, MLflow, Vertex AI pipelines, ArgoCD, CI/CD for ML). Data Engineering: Spark, Kafka, Flink, Airflow. Deep knowledge of cloud platforms: GCP, AWS, Azure. Implement ML pipelines using platforms such as Vertex AI, Red Hat OpenShift AI, and Kubeflow. Experience with Agentic AI frameworks for orchestrating autonomous agents and multi-step workflows. Strong skills in API integration, microservices, and distributed systems.
Nice to Have
Familiarity with telecom data products and autonomous networks use cases and Ab-intio data management platform Experience in data mesh, data fabric, and modern data architectures. Knowledge of vector databases and retrieval-augmented generation (RAG). Understanding of security, compliance, and governance for LLM/GenAI deployment. Contributions to open-source AI/ML or GenAI frameworks. Exposure to TM Forum, 3GPP standards, and telecom AI frameworks.
What We Offer
Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered. About Inclusion and Equal Opportunity
Nokia is committed to inclusion and is an equal opportunity employer. Nokia defines and champions inclusive practices and has received recognitions for inclusion & equality, including: One of the World's Most Ethical Companies by Ethisphere Gender-Equality Index by Bloomberg Workplace Pride Global Benchmark
At Nokia, we act inclusively and respect the uniqueness of people. Employment decisions are made without regard to 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. Join us and be part of a company where you will feel included and empowered to succeed. Additional Information
US/Canada Corporate Retirement Savings Plan Health and dental benefits Short-term disability and long-term disability Life insurance and AD&D - Company paid 2x base pay Optional or Supplemental life and AD&D insurance (Employee/Spouse/Child) Paid time off for holidays and vacation Employee Stock Purchase Plan Tution Assistance Plan Adoption assistance Employee Assistance Program/Work Life Resource Program
The above benefits exclude students. Disclaimer for US/Canada Nokia Maintains broad annual base salary ranges for its roles in order to account for variations in knowledge, skills, experience and market conditions, and with consideration to internal peer equity. (Check the salary ranges in the job info section for this role) All North America job posts will post for a minimum of 7 calendar days and up to 180 days or until candidate/s identified. #J-18808-Ljbffr
We are seeking a highly skilled AI/ML Domain Architect to design, deploy, and operationalize advanced AI/ML solutions with a focus on MLOps, Generative AI (GenAI), LLM Ops, and Agentic AI integration. This role requires deep expertise in ML engineering practices, cloud-native deployment, and hands-on experience with modern AI platforms. The engineer will be responsible for building scalable ML pipelines, LLM-based applications, and intelligent agent frameworks to accelerate delivery for telecom, enterprise, and next-generation autonomous network solutions. Responsibilities Design, optimize, and scale end-to-end ML pipelines using ML-Ops best practices, including CI/CD, model deployment, and performance monitoring. Develop and operationalize Gen AI/LLM-based solutions, applying techniques such as fine-tuning, prompt engineering, Retrieval-Augmented Generation (RAG), and LLM observability. Integrate Agentic AI frameworks with existing AI/ML systems to enable autonomous decision-making and intelligent workflow orchestration. Implement robust data pipelines for ingestion, preprocessing, and feature engineering across structured, semi-structured, and unstructured data sources. Collaborate cross-functionally with data scientists, solution architects, and delivery teams to translate AI/ML use cases into scalable, production-ready solutions. Design and manage cloud-native AI/ML infrastructure on platforms like Google Cloud (Vertex AI), Red Hat OpenShift AI, and Kubeflow. Deploy scalable AI solutions across multi-cloud and hybrid environments using Kubernetes and container orchestration. Ensure observability and governance of AI systems, including model drift detection, fairness, compliance, and LLM usage guardrails. Create accelerators, reusable frameworks, and automation tools to reduce time-to-market and enhance delivery efficiency. Support customer engagements through proof-of-concepts (PoCs), pilot implementations, and production rollouts.
You Have
Bachelor's/Master's in Computer Science, Data Engineering, AI/ML, or related field. 10+ years of experience in AI/ML engineering, including 5+ years in MLOps. Proven experience with LLM platforms and GenAI ecosystems (OpenAI, Anthropic, Vertex AI, Hugging Face, LangChain, LlamaIndex). Strong proficiency in Python, PyTorch, TensorFlow, Scikit-learn, SQL. Expertise in MLOps pipelines (Kubeflow, MLflow, Vertex AI pipelines, ArgoCD, CI/CD for ML). Data Engineering: Spark, Kafka, Flink, Airflow. Deep knowledge of cloud platforms: GCP, AWS, Azure. Implement ML pipelines using platforms such as Vertex AI, Red Hat OpenShift AI, and Kubeflow. Experience with Agentic AI frameworks for orchestrating autonomous agents and multi-step workflows. Strong skills in API integration, microservices, and distributed systems.
Nice to Have
Familiarity with telecom data products and autonomous networks use cases and Ab-intio data management platform Experience in data mesh, data fabric, and modern data architectures. Knowledge of vector databases and retrieval-augmented generation (RAG). Understanding of security, compliance, and governance for LLM/GenAI deployment. Contributions to open-source AI/ML or GenAI frameworks. Exposure to TM Forum, 3GPP standards, and telecom AI frameworks.
What We Offer
Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered. About Inclusion and Equal Opportunity
Nokia is committed to inclusion and is an equal opportunity employer. Nokia defines and champions inclusive practices and has received recognitions for inclusion & equality, including: One of the World's Most Ethical Companies by Ethisphere Gender-Equality Index by Bloomberg Workplace Pride Global Benchmark
At Nokia, we act inclusively and respect the uniqueness of people. Employment decisions are made without regard to 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. Join us and be part of a company where you will feel included and empowered to succeed. Additional Information
US/Canada Corporate Retirement Savings Plan Health and dental benefits Short-term disability and long-term disability Life insurance and AD&D - Company paid 2x base pay Optional or Supplemental life and AD&D insurance (Employee/Spouse/Child) Paid time off for holidays and vacation Employee Stock Purchase Plan Tution Assistance Plan Adoption assistance Employee Assistance Program/Work Life Resource Program
The above benefits exclude students. Disclaimer for US/Canada Nokia Maintains broad annual base salary ranges for its roles in order to account for variations in knowledge, skills, experience and market conditions, and with consideration to internal peer equity. (Check the salary ranges in the job info section for this role) All North America job posts will post for a minimum of 7 calendar days and up to 180 days or until candidate/s identified. #J-18808-Ljbffr