AI/ML Solution Architect
Skills required
About this role
In the AI/ML Solution Architect role, you will collaborate in a dynamic, cross-functional team environment that fosters innovation and creativity. You will work alongside skilled data scientists, engineers, and business stakeholders to tackle complex challenges and drive impactful AI/ML solutions in manufacturing operations. Our culture prioritizes continuous learning, enabling you to stay ahead of emerging technologies and methodologies. Enjoy a flexible work-life balance with opportunities for remote work. You'll have access to professional development programs and certifications to enhance your expertise. Competitive compensation and comprehensive benefits ensure your contributions are valued, while a diverse and inclusive workplace empowers you to make a meaningful impact on projects that shape the future of technology at Nokia.
Responsibilities
- Design and implement end-to-end scalable AI/ML solutions, including data pipelines and model deployment.
- Define and optimize secure architectures for ML workloads in cloud and on-prem environments.
- Collaborate with business leaders to identify AI/ML opportunities and develop solution roadmaps.
- Provide technical leadership in AI governance, best practices, and emerging technologies.
- Architect MLOps pipelines for CI/CD, model versioning, and lifecycle management.
- Ensure data quality, governance, and compliance throughout the AI/ML processes.
- Act as a liaison between data scientists, engineers, and business stakeholders to drive successful outcomes.
- Lead design reviews and architecture discussions to support strategic AI initiatives.
Qualifications
Must-Have:
- Bachelors / Master degree in computer science, data science, AI or related field with 10+ years in software engineering, data engineering or architecture roles
- 5+ years hands-on experience in AI/ML solutions in production environments
- Familiar with machine learning algorithms (supervised, unsupervised, deep learning) and with edge AI, IoT analytics, or real-time ML systems
- Experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn
- Proficiency in Python with familiarity in Java/Scala
- Hands-on experience with cloud platforms like Azure, AWS, or GCP
- Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker
- Exposure to Generative AI, NLP, and LLM-based applications
Nice-To-Have:
- Certifications in cloud platforms or AI/ML specialties
- Experience in manufacturing, telecom, or digital transformation domains
