Lead Engineering Manager

This role is for one of the Weekday's clients

Salary range: Rs 400000 - Rs 600000 (ie INR 4-6 LPA)

Requirements

Key Responsibilities

• Lead and manage multiple engineering teams working on machine learning platforms, services, and applications
• Own the end-to-end delivery of ML-powered products, from concept and design to deployment and scaling
• Drive architectural decisions for scalable, reliable, and secure ML systems in production environments
• Collaborate with data scientists to productionize models, ensuring robustness, performance, and monitoring
• Define engineering roadmaps aligned with business goals and long-term ML strategy
• Establish best practices for ML system design, experimentation, deployment, and lifecycle management
• Ensure high engineering standards through code reviews, design reviews, and technical mentorship
• Build and maintain ML infrastructure, including training pipelines, inference systems, and data workflows
• Oversee integration of ML solutions with existing platforms, APIs, and distributed systems
• Partner with product leaders to translate business problems into ML-driven solutions
• Drive adoption of DevOps and MLOps practices, including CI/CD, automation, and observability
• Manage project execution, timelines, and cross-team dependencies across large programs
• Hire, coach, and develop senior engineers and managers to build strong succession pipelines
• Foster a culture of innovation, ownership, operational excellence, and continuous improvement
• Ensure systems meet requirements for scalability, reliability, security, and compliance
• Communicate technical vision, trade-offs, and progress clearly to senior leadership
  

What Makes You a Great Fit

• 14+ years of overall engineering experience with significant leadership responsibility
• Proven experience leading large engineering teams delivering machine learning systems at scale
• Strong foundation in machine learning concepts, model development, and real-world deployment challenges
• Hands-on experience building and operating production ML platforms and services
• Deep understanding of distributed systems, data pipelines, and cloud-based architectures
• Experience partnering with data science, product, and business teams in complex environments
• Ability to balance technical depth with people leadership and strategic thinking
• Strong problem-solving skills with a bias for action and measurable outcomes
• Experience defining engineering processes, quality standards, and operational metrics
• Excellent communication skills to influence stakeholders across technical and non-technical domains
• Track record of mentoring senior engineers and building high-performing teams
• Comfortable operating in fast-paced, ambiguous environments with high ownership
• Strong judgment in making architectural and prioritization decisions at scale
• Passion for leveraging machine learning to solve complex, real-world problems