- Company Name
- DXC Technology
- Job Title
- ML/AI Architect
- Job Description
-
**Job Title**
ML/AI Architect
**Role Summary**
Lead the design and deployment of advanced AI systems, including large language models (LLMs) and agent-based architectures, ensuring high performance, safety, and alignment with business objectives. Provide technical leadership to data science and engineering teams in end‑to‑end AI solution delivery across cloud and distributed environments.
**Expectations**
- Own AI strategy and execution for client programs.
- Deliver robust, scalable AI solutions that meet reliability, ethical, and regulatory standards.
- Drive continuous improvement through MLOps best practices and model monitoring.
- Collaborate with cross‑functional stakeholders to translate business needs into AI architecture.
**Key Responsibilities**
- Develop and lead AI strategies, including LLMs, transformer models, and retrieval‑augmented generation (RAG).
- Design AI components: LLM integration, vector databases, agent frameworks, and pipeline optimization.
- Establish evaluation protocols, performance metrics, and safety checks for AI models.
- Architect MLOps pipelines for continuous training, testing, and deployment in cloud or on‑premise environments.
- Set technical standards for model architecture, data engineering, and infrastructure.
- Guide teams on AI toolchains, version control, CI/CD, and automated deployment.
- Mentor data science, ML engineering, and product teams on AI best practices.
**Required Skills**
- Programming: Python; ML frameworks – TensorFlow, PyTorch.
- AI expertise: NLP, transformers, reinforcement learning, large‑scale model training.
- MLOps: CI/CD, model versioning, containerization, orchestration.
- Data engineering: ETL, feature engineering, vector databases (e.g., FAISS, Milvus).
- Evaluation: performance metrics, bias mitigation, safety checks, compliance.
- Mathematical foundation: linear algebra, calculus, statistics.
- Collaboration: cross‑functional team leadership, requirement gathering, stakeholder communication.
**Required Education & Certifications**
- Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning or related field.
- Proven experience building or fine‑tuning LLMs and transformer‑based systems.
- Demonstrated deployment of AI solutions at scale (cloud or distributed).
- Familiarity with regulatory and ethical AI practices.