Talent.com
AI Architect

AI Architect

ConfidentialMumbai, Kolkata, Thane
9 hours ago
Job description

Job Description

Role

  • AI Architect

Desired Experience Range 12 to 15 years

Location of Requirement Pan India-

Desired Skills -Technical / Behavioral

Must-Have

  • AI / ML Expertise : Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, LangChain.
  • Cloud & DevOps : Experience with AWS SageMaker, Azure ML, Google Vertex AI, Docker, Kubernetes, CI / CD.
  • Big Data & Databases : Expertise in Hadoop, Spark, Kafka, SQL, NoSQL, Snowflake, Delta Lake.
  • MLOps & AI Deployment : Hands-on experience with MLflow, Kubeflow, Airflow, FastAPI, Flask, Streamlit.
  • AI Security & Compliance : Deep understanding of model interpretability, AI ethics, adversarial attacks, governance.

    • Good-to-Have

  • Experience with Generative AI & LLMs (GPT, LLaMA, Stable Diffusion, DALL
  • E, etc.).
  • Knowledge of Edge AI & AI-powered IoT solutions.
  • Experience with AutoML tools like Google AutoML, H2O.ai, DataRobot.
  • Familiarity with quantization, pruning, and optimization techniques for AI model efficiency.
  • Hands-on experience with vector databases (FAISS, Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) architectures.
  • Knowledge of Reinforcement Learning (RL), Bayesian Methods, and Time-Series Forecasting.
  • Experience with Graph Neural Networks (GNNs) and AI in cybersecurity.
  • Exposure to Blockchain & AI integration for secure and decentralized AI applications.
  • Familiarity with natural language processing (NLP) frameworks like Hugging Face Transformers

    • Responsibility of / Expectations from the Role

  • AI Strategy & Architecture Development
  • Define and implement an enterprise AI architecture that aligns with business goals and IT strategies.
  • Develop AI roadmaps, best practices, and governance frameworks to ensure scalability, security, and efficiency.
  • Evaluate, recommend, and integrate cutting-edge AI / ML frameworks, tools, and platforms (AWS, Azure, GCP).
  • Establish best practices for MLOps, AI governance, and ethical AI practices.
  • AI Model Development & Deployment
  • Lead the design, development, and optimization of machine learning, deep learning, and generative AI solutions.
  • Oversee data preprocessing, feature engineering, and model optimization to ensure accuracy and efficiency.
  • Implement MLOps pipelines for model training, deployment, monitoring, and continuous improvement.
  • Work with software engineers to integrate AI solutions into production environments seamlessly.
  • Data Engineering & AI Infrastructure
  • Collaborate with data engineering teams to design robust data pipelines, warehouses, and lakes for AI consumption.
  • Optimize real-time and batch data processing architectures for AI model performance.
  • Ensure AI infrastructure is scalable, cost-effective, and cloud-native where applicable.

    • AI Governance, Security & Compliance

  • Establish AI governance frameworks to ensure models are explainable, fair, and aligned with ethical standards.
  • Ensure compliance with global data privacy laws (GDPR, HIPAA) and AI risk management frameworks.
  • Monitor AI models for bias, drift, and performance degradation and implement proactive mitigation strategies.
  • Leadership & Collaboration
  • Act as a strategic advisor to executives and stakeholders on AI adoption and innovation.
  • Provide technical leadership and mentorship to AI engineers, data scientists, and cross-functional teams.
  • Conduct knowledge-sharing sessions, drive AI training initiatives, and foster a culture of AI excellence.

    • Skills Required

    Tensorflow, Pytorch

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