AI & Machine Learning Lead Architect

AI/ML/NLP Architect

Job Summary

AI/ML/NLP Architect

Key Responsibilities

• Architect Core Platform:

  Design scalable, modular AI/ML/NLP architecture integrating with ERP systems (SAP, Oracle, Microsoft Dynamics).

• Lead Model Development:

  Oversee ML model design for analytics, anomaly detection, and optimization; implement NLP for intelligent automation and conversational interfaces.

• End-to-End Execution:

  Manage lifecycle from prototype to production—data pipelines, deployment, monitoring, and continuous improvement.

• Governance & Compliance:

  Ensure AI ethics, data privacy (GDPR/CCPA), explainability, and security.

• Collaborate & Mentor:

  Align solutions with business needs, guide teams, and mentor AI engineers.

• Innovate & Optimize:

  Explore emerging AI trends (GenAI, federated learning) and drive performance optimization using cloud-native tools (AWS, Azure, GCP, Kubernetes).

• Documentation:

  Develop architecture blueprints, roadmaps, and technical documentation.

Qualifications

• Education:

  Bachelor’s/Master’s in Computer Science, Data Science, AI, or related field (PhD preferred).

• Experience:

  8+ years in AI/ML/NLP roles (3+ in enterprise-grade AI architecture). Proven record in ERP, SaaS, or financial AI products.

• Technical Skills:

• Expertise in TensorFlow, PyTorch, Scikit-learn, and NLP libraries (Transformers, spaCy).
• Strong knowledge of cloud AI (SageMaker, Vertex AI), orchestration (Airflow, Kubeflow), and vector DBs (FAISS, Pinecone).
• MLOps, CI/CD, model versioning, and A/B testing proficiency.
  

• Soft Skills:

  Excellent problem-solving, communication, and leadership abilities.

Preferred

• Experience in ERP AI use cases (finance, supply chain).
• Familiarity with agentic AI (LangChain, AutoGen) and LLMs (GPT, Llama).
• Open-source or research contributions (NeurIPS, ACL).
• Agile/Scrum experience with Jira or Confluence.