๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ญ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ญ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ญ๐ฌ-๐ญ๐ฌ๐ฌ ๐๐ฃ๐)
Experience: 3+ yrs
Location: India
Job Type: Full-time
We are seeking an experiencedย Engineering Managerย to lead high-performing engineering teams focused on building scalable, production-gradeย Machine Learningย 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 toย Machine Learningย 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.