AI Architect

• AI Strategy Development: Develop a strategic vision and roadmap for AI initiatives, aligning with Rhythm Innovations' objectives and long-term goals.
  
• Solution Architecture: Design scalable, secure, and efficient AI/ML architectures tailored to our SaaS offerings and customer needs.
  
• Technology Evaluation: Identify and recommend appropriate tools, frameworks, and platforms for AI development, deployment, and integration.
  
• Data Pipeline Management: Collaborate with data engineering teams to establish robust data pipelines and ensure data quality for AI modeling.
  
• Model Development and Optimization: Lead the design, training, and optimization of AI/ML models for applications such as predictive analytics, anomaly detection, and natural language processing (NLP).
  
• Integration and Deployment: Oversee the seamless integration of AI solutions into existing platforms and ensure scalability, reliability, and performance.
  
• Governance and Compliance: Establish AI best practices, model governance protocols, and compliance with ethical AI standards and relevant regulations.
  
• Team Leadership: Mentor a team of AI engineers and data scientists, fostering a culture of collaboration, innovation, and excellence.
  
• Performance Monitoring: Implement monitoring systems for deployed models, ensuring they deliver accurate, actionable results while continuously improving their performance.
  

Requirements

• Bachelor's in engineering in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. A Ph.D. is an added advantage.
  

• 10 to 12 years of experience in AI/ML development, including 3+ years in an architect or leadership role.
  
• Proven expertise in delivering enterprise-scale AI solutions, preferably in SaaS or supply chain domains.
  

• Strong proficiency in Gen AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  
• Advanced knowledge of programming languages such as Python, R, or Java.
  
• Experience with cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services.
  
• Familiarity with big data technologies (Hadoop, Spark, Kafka) and databases (SQL/NoSQL).
  
• Proficiency in MLOps practices for model deployment and management.
  
• Specialized knowledge in AI domains such as computer vision, NLP, or predictive analytics.
  

• Strategic and analytical mindset with strong problem-solving skills.
  
• Excellent communication and stakeholder management capabilities.
  
• Leadership qualities with the ability to inspire and mentor teams.