AI / ML Architect

AI / ML Architect Experience: 8-14+ Years Location: Bengluru (Remote) Notice Period : Immediate Joiner Role Overview We are looking for an experienced AI / ML Architect/Lead to design, develop, and deploy enterprise-scale AI/ML and Generative AI solutions. The ideal candidate will have strong expertise in Machine Learning, Data Engineering, MLOps, LLMs, RAG architectures, and Cloud-based AI platforms, with the ability to lead end-to-end AI initiatives. Key Responsibilities • Design and architect scalable AI/ML and Generative AI solutions. • Develop data pipelines, ETL/ELT processes, and feature engineering frameworks. • Perform data preprocessing, EDA, model training, optimization, and deployment. • Implement MLOps practices including model versioning, experimentation,monitoring, and CI/CD. • Build and deploy RAG-based applications, AI agents, and LLM-powered solutions. • Collaborate with business and technical stakeholders to translate requirements into AI solutions. • Ensure AI security, governance, compliance, and best practices. • Mentor and guide ML Engineers, Data Scientists, and AI teams. Qualifications • Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field. • 8-14+ years of experience in AI/ML architecture and solution delivery. • Proven experience building enterprise-scale AI, ML, and Generative AI applications. • Strong leadership and stakeholder management skills. Requirements Required Skills AI/ML & GenAI • Machine Learning Algorithms • Feature Engineering, Data Splitting, Encoding • Model Design, Optimization & Deployment • LLMs: OpenAI, LLaMA, Gemini, BERT • RAG Pipelines, Prompt Engineering • AI Agent Frameworks & Agent Deployment Programming & Frameworks • Python, R, Scala, Java • Pandas, TensorFlow, PyTorch, Scikit-learn, Keras Data & MLOps • Data Engineering, ETL/ELT • Git, DVC, MLflow • Docker, Kubernetes, Kubeflow • Apache Airflow, CI/CD Cloud & Platforms • AWS, Azure, GCP • AWS SageMaker, AWS Bedrock • Azure Machine Learning Services • Google AI Platform • Databricks, Snowflake, Salesforce, SAP Databases • RDBMS & NoSQL Databases • Vector Databases (Pinecone, Weaviate, Chroma, FAISS, Milvus, etc.)