Artificial Intelligence/Machine Learning Architect

4 days ago

Hyderabad, Telangana, India beBeeMachineLearning Full time US$ 1,50,000 - US$ 2,20,000
AI/ML Practice Lead

Seeking a seasoned AI/ML practice lead who combines deep expertise in machine learning with strong solutioning skills.

We're looking for an architect who can engage clients, design scalable AI/ML solutions and lead or contribute to technical implementation.

Key Responsibilities:
  1. 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 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.

  1. Pre-Sales & Solution Engineering

Collaborate with sales teams to understand client needs and propose ML/AI solutions. Lead technical discovery, 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.

  1. Cloud & MLOps Integration

Architect solutions using cloud platforms (GCP, AWS, Azure). Deploy ML models using containerization and orchestration tools. Implement MLOps workflows: model versioning, CI/CD pipelines, monitoring, and retraining.

  1. 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:
  1. 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.

  1. 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.

  1. Cloud & MLOps

Hands-on experience with cloud platforms and MLOps tools: GCP Vertex AI, AWS SageMaker, Azure ML, MLflow, Kubeflow, Airflow, GitHub Actions, Docker, Kubernetes.

  1. 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.

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