Engineering Manager

Weekday AI (YC W21)Delhi, India
LinkedInPosted 16h agoOriginal Listing

Job Description

๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐—ผ๐—น๐—ฒ ๐—ถ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ผ๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ช๐—ฒ๐—ฒ๐—ธ๐—ฑ๐—ฎ๐˜†'๐˜€ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€ ๐—ฆ๐—ฎ๐—น๐—ฎ๐—ฟ๐˜† ๐—ฟ๐—ฎ๐—ป๐—ด๐—ฒ: ๐—ฅ๐˜€ ๐Ÿญ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ - ๐—ฅ๐˜€ ๐Ÿญ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ (๐—ถ๐—ฒ ๐—œ๐—ก๐—ฅ ๐Ÿญ๐Ÿฌ-๐Ÿญ๐Ÿฌ๐Ÿฌ ๐—Ÿ๐—ฃ๐—”) Experience: 3+ yrs Location: India Job Type: Full-time We are seeking an experienced Engineering Manager to lead high-performing engineering teams focused on building scalable, production-grade Machine Learning solutions. This role is ideal for professionals who combine strong technical expertise in machine learning with proven leadership skills to drive engineering excellence, mentor teams, and deliver innovative AI-powered products. As an Engineering Manager, you will oversee the design, development, deployment, and optimization of machine learning systems while collaborating closely with Product, Data Science, Platform Engineering, and Business stakeholders. You will be responsible for establishing engineering best practices, enabling technical innovation, and ensuring the successful delivery of reliable, scalable, and impactful ML solutions. This role requires a balance of technical depth, people leadership, and strategic thinking to align engineering efforts with business objectives. Requirements Key Responsibilities - Lead, mentor, and grow engineering teams building machine learning products and AI-driven applications - Drive the design, development, deployment, and maintenance of scalable machine learning systems and production pipelines - Collaborate with Data Scientists, ML Engineers, Product Managers, and cross-functional teams to translate business requirements into technical solutions - Establish engineering standards, development processes, and best practices for software quality, machine learning operations, and system reliability - Oversee project planning, resource allocation, sprint execution, and technical delivery to ensure successful outcomes - Guide architectural decisions for ML platforms, data pipelines, model serving, and cloud-based infrastructure - Improve model deployment, monitoring, performance optimization, and lifecycle management using MLOps principles - Conduct code reviews, technical design discussions, and mentoring sessions to elevate engineering quality and team capabilities - Track engineering metrics, identify risks, and drive continuous improvements in productivity, scalability, and operational efficiency - Foster a culture of innovation, collaboration, accountability, and continuous learning across engineering teams What Makes You a Great Fit - 3+ years of experience in software engineering with significant exposure to Machine Learning systems and engineering leadership - Proven experience managing engineering teams while delivering production-grade AI or machine learning solutions - Strong understanding of machine learning workflows, model deployment, MLOps, data engineering, and cloud-native architectures - Experience working with Python, ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies - Familiarity with cloud platforms, containerization, CI/CD pipelines, Kubernetes, and scalable infrastructure for ML workloads - Strong knowledge of software architecture, distributed systems, API development, and engineering best practices - Excellent leadership, mentoring, stakeholder management, and cross-functional collaboration skills - Strong analytical thinking, problem-solving abilities, and a data-driven approach to technical decision-making - Ability to balance technical execution with strategic planning, people management, and business priorities - Passion for building high-performing engineering teams, driving innovation, and delivering impactful machine learning products at scale

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