About Lexmark:
Lexmark is now a proud part of Xerox, bringing together two trusted names and decades of expertise into a bold and shared vision.
When you join us, you step into a technological ecosystem where your ideas, skills, and ambition can shape what comes next. Whether you’re just starting out or leading at the highest levels, this is a place to grow, stretch, and make real impact—across industries, countries, and careers.
From engineering and products to digital services and customer experience, you’ll help connect data, devices, and people in smarter, faster ways. This is meaningful, connected work—on a global stage, with the backing of a company built for the future, and a robust benefits package designed to support your growth, well-being, and life beyond work.
Job Description:
We are on a mission to drive innovation and transformation in Data engineering through the use of Artificial Intelligence (AI) and Machine Learning (ML) across the organization. We are looking for experienced professionals who bring deep technical expertise, a problem-solving mindset, and the curiosity to explore what’s next in the AI landscape.
As part of this journey, you will help define, shape, and deliver impactful AI initiatives — from exploring Generative and Agentic AI capabilities to developing intelligent applications that benefit IT and other business functions, creating measurable business value. This role is ideal for someone who thrives in ambiguity, enjoys experimenting with emerging technologies, and is motivated to build practical, global scalable AI solutions.
Key Responsibilities:
Design and implement robust data pipelines that support data preprocessing, model training, and deployment.
Ensure that the data pipeline is optimized for high-volume and high-velocity data required by ML models.
Build and manage feature stores that can efficiently store, retrieve, and serve features for ML models.
Collaborate with cross-functional teams to implement solutions where AI can deliver business impact.
Design, develop, and operationalize AI/ML solutions using modern frameworks, tools, and cloud platforms.
Core Competencies
Data Engineering: Hands on experience on Databricks, Azure data factory, ETL/ELT and Data Warehouse knowledge, Python, PySpark, Strong SQL skills
Cloud Platforms: Azure (must), Amazon (Good to have)
Languages: Python, SQL, Scala, Bash
DevOps & Infra: CI/CD pipelines(must) , Docker, Kubernetes, Terraform (Good to have)
ML/AI Integration: MLflow, Feature Store, TensorFlow, PyTorch, Hugging Face (Good to have)
GenAI: OpenAI API, Vector DBs (Good to have)
Required Skills & Qualifications:
Nice to Have:
Experience with MLOps, cloud AI platforms, and containerization tools (e.g., Docker, Kubernetes).
Who You Are:
You’re an engineer with a curious mind and a builder’s spirit — eager to explore how AI can reshape the way we work and think. You bring expertise, adaptability, and drive to collaborate in an evolving environment where the mission is being defined and the possibilities are wide ope
