Lead Engineering Manager

6 days ago


Navi Mumbai, India Weekday AI Full time

This role is for one of the Weekday's clients Salary range: Rs - Rs (ie INR 4-6 LPA) Min Experience: 14 years Location: India JobType: full-time As a Lead Engineering Manager – Machine Learning, you will play a pivotal leadership role in building and scaling high-impact, production-grade machine learning systems that power data-driven products and platforms. This role combines deep technical expertise in machine learning with strong people leadership, strategic thinking, and execution excellence. You will lead multiple engineering teams, shape the long-term ML technology vision, and partner closely with product, data science, and business stakeholders to deliver scalable, reliable, and innovative solutions. Operating in a fast-paced environment, you will drive engineering best practices, foster a culture of innovation, and ensure that machine learning capabilities translate into measurable business outcomes. 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



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