Job Description:

Core Responsibilities of an AI Engineer

Must have

Integrate CI/CD pipelinesManage containers (e.g., Docker, Kubernetes)Automate deployment and scaling processesModel 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 teams—software engineers, data scientists, product managers—to 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. We’re committed to fostering an inclusive environment where everyone can thrive.

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