AI Engineer

Job Description:

Core Responsibilities of an AI Engineer

Must have

• Integrate CI/CD pipelines
• Manage containers (e.g. Docker Kubernetes)
• Automate deployment and scaling processes
• Model Development & Deployment: Build scalable AI/ML models for real-world applications including NLP computer vision and GenAI use cases123.
• Data Engineering: Preprocess large-scale structured and unstructured datasets optimize pipelines and extract insights7.
• MLOps & Automation: Implement best practices for training deployment and monitoring of AI systems using tools like MLflow Docker and cloud platforms (AWS Azure GCP)4.

Good to have

• Collaboration: Work with cross-functional teamssoftware engineers data scientists product managersto integrate AI into products1.
• Research & Innovation: Stay updated with the latest AI trends research papers and tools (e.g. LangChain RAG LLMs)5.
• Mentorship: Guide junior engineers and contribute to team development3.

Skills & Qualifications

• Programming: Strong in Python with experience in TensorFlow PyTorch Scikit-learn and data manipulation libraries (Pandas NumPy)
• AI Concepts: Deep understanding of supervised/unsupervised learning NLP deep learning and GenAI.
• Tools & Frameworks: Experience with vector databases containerization orchestration and prompt engineering.

Soft Skills: Critical thinking stakeholder engagement conflict management and team building

At DXC Technology we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing productivity individual work styles and life circumstances. Were committed to fostering an inclusive environment where everyone can thrive.

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