Data Scientist/Architect

Role : AI/ML Architect Experience : 8 - 12 Years Qualification : Bachelors/Masters/PhD in Data Science, Machine Learning, Artificial Intelligence, Engineering, or related fields Location : Noida Employment Type : Full-time Role Overview : Repro is looking for a highly experienced AI/ML Architect to design, scale, and govern enterprise-grade machine learning solutions. This role focuses on solution design, system architecture, and end-to-end ML lifecycle ownership, while mentoring senior data scientists and engineers. The ideal candidate will bridge data science and engineering to deliver scalable, production-ready AI systems. Key Responsibilities : - Architect end-to-end machine learning systems, from data ingestion to model deployment and monitoring - Design and review scalable, high-performance ML architectures for large-scale production environments - Define and implement best practices for the ML lifecycle, including training, validation, deployment, versioning, and monitoring - Lead architecture decisions for model scaling, performance optimization, and reliability - Collaborate closely with data engineers and platform teams to ensure seamless integration - Establish standards for reusability, modularity, and maintainability of AI/ML components - Guide the adoption of feature stores, model registries, and data lakes - Mentor senior data scientists and ML engineers on solution design, architecture patterns, and production readiness - Review technical designs, conduct architecture walkthroughs, and provide technical governance Technical Skills & Expertise : Core AI/ML Skills : - Strong proficiency in Python - Hands-on experience with TensorFlow and/or PyTorch - Deep understanding of deep learning architectures and model optimization - Experience with distributed data processing using Spark MLOps & Platform : - Strong knowledge of MLOps practices (CI/CD for ML, model versioning, monitoring, retraining) - Experience with model registries, feature stores, and experiment tracking tools - Exposure to data lakes and large-scale data platforms Cloud & Tools : - Hands-on experience with cloud AI platforms such as : 1. AWS Bedrock & SageMaker 2. Azure Machine Learning 3. Google Cloud AI / Vertex AI - Strong understanding of cloud-native architectures and scalable ML deployments Key Focus Areas : - AI/ML solution design and system architecture - Scalability, performance, and reliability of ML systems - Enterprise-grade ML lifecycle management - Cross-team collaboration and technical leadership Desired Profile : - 8 - 12 years of overall experience in AI/ML, with significant exposure to architecture and solution design - Proven experience designing and deploying production-scale ML systems - Strong mentoring and technical leadership skills - Ability to translate business problems into robust AI architectures - Comes from a product company and made significant contributions in automating processes using AI - Spend 60 - 70% of time in coding in the Individual capacity.