AI/ML Architect

Job Overview:

AI/ML Architect

Key Responsibilities:

AI/ML Architecture & Hands-on Delivery

• Design and implement end-to-end machine learning systems (data ingestion, feature engineering, model development, deployment, monitoring).
• Write clean, production-grade Python code for ML pipelines, APIs, and utilities.
• Develop and fine-tune models using Scikit-learn, TensorFlow, PyTorch, or Hugging Face.
• Design solutions for GenAI, NLP, computer vision, and recommendation systems.

Pre-Sales & Solution Engineering

• Collaborate with sales and business teams to understand client needs and propose ML/AI solutions.
• Lead technical discovery, client workshops, and PoC scoping sessions.
• Respond to RFPs/RFIs with solution architecture, estimation, and tech write-ups.
• Prepare and deliver engaging demos and technical presentations to CXOs and IT leaders.

Cloud & MLOps Integration

• Architect solutions using GCP (Vertex AI), AWS (SageMaker), or Azure (ML Studio).
• Deploy ML models using Docker, Kubernetes, FastAPI, or Flask.
• Implement MLOps workflows: model versioning, CI/CD pipelines, monitoring, and retraining.

Leadership & Collaboration

• Provide mentorship and technical guidance to junior data scientists and engineers.
• Stay current with advancements in AI/ML, GenAI, and tooling.
• Support delivery teams during project execution as a solution overseer or active contributor.

Required Skills:

Machine Learning & AI

• Strong grounding in ML fundamentals, supervised/unsupervised learning, and deep learning.
• Practical experience with NLP, GenAI (e.g., LLMs, RAG), time series, or image processing.

Programming (Python-first)

• Expert in Python for data science and backend integration.
• Familiar with Jupyter, Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, Hugging Face.
• Experience building APIs with FastAPI/Flask and integrating ML into applications.

Cloud & MLOps

• Hands-on experience with any of: GCP Vertex AI, AWS SageMaker, or Azure ML.
• MLOps tools: MLflow, Kubeflow, Airflow, GitHub Actions, Docker, Kubernetes.

Pre-Sales & Client Engagement

• Experience leading technical discovery, PoCs, RFP responses, and stakeholder presentations.
• Ability to translate business problems into AI/ML solutions and articulate ROI.