Key Responsibilities

1. Technology Strategy & Leadership

- Define and execute the company's long-term technology roadmap in alignment with business goals.
- Evaluate emerging technologies, tools, platforms, and architectures relevant to robotics and industrial automation.
- Make key technical decisions related to system architecture, technology selection, scalability, and product reliability.
- Establish engineering standards, development practices, documentation requirements, and technology governance.
- Identify opportunities for innovation, automation, cost reduction, and product differentiation.

2. Robotics & Product Development

- Lead the design, development, integration, and improvement of robotics-based products and systems.
- Oversee the integration of mechanical assemblies, electrical systems, actuators, sensors, controllers, and robotic mechanisms.
- Guide the development of robot control software, motion planning, perception systems, and hardware-software interfaces.
- Ensure products meet performance, reliability, safety, maintainability, and operational requirements.
- Drive product development from proof of concept and prototyping through testing, production readiness, and field deployment.

3. AI, Machine Learning & Computer Vision

- Lead the development and integration of AI/ML and computer vision capabilities into robotics products.
- Oversee image acquisition, data collection, annotation, dataset quality, model training, validation, and deployment.
- Define processes for model monitoring, performance evaluation, retraining, and continuous improvement.
- Ensure AI models perform reliably under real-world conditions, including changing lighting, materials, speeds, and operating environments.
- Guide the deployment of vision systems and AI inference solutions on cloud, edge, and in office infrastructure.

4. Engineering Team Management

- Lead and mentor robotics, software, computer vision, AI/ML, mechanical, electrical, and automation engineering teams.
- Define team structures, technical ownership, responsibilities, and reporting mechanisms.
- Set engineering priorities, project milestones, technical deliverables,



and quality expectations.
- Conduct technical reviews, architecture reviews, design reviews, and performance assessments.
- Build a culture of accountability, collaboration, innovation, and continuous learning.

5. System Integration & Deployment

- Ensure seamless integration of robotics hardware, software, AI models, sensors, controllers, and industrial systems.
- Oversee factory acceptance testing, site acceptance testing, commissioning, and performance validation.
- Lead technical troubleshooting and root-cause analysis for failures occurring during development or deployment.
- Establish processes for field monitoring, preventive maintenance, upgrades, and technical support.
- Ensure deployed systems meet agreed performance and operational requirements.

6. Project & Product Delivery

- Translate business requirements and customer needs into technical specifications and executable development plans.
- Establish project timelines, milestones, resource requirements, and delivery priorities.
- Coordinate with project management, operations, procurement, vendors, and client-facing teams on technical dependencies.
- Monitor development progress, resolve technical bottlenecks, and manage delivery risks.
- Ensure timely delivery without compromising product quality, safety, or reliability.

7. Infrastructure, Quality & Reliability

- Oversee engineering infrastructure, source-code management, CI/CD, testing automation, and release management.
- Establish standards for software quality, hardware validation, cybersecurity, data security, and system reliability.
- Guide cloud and edge infrastructure for AI workloads, data pipelines, model deployment, and system monitoring.
- Define product performance metrics, uptime targets, failure analysis processes,



and reliability improvement plans.
- Ensure technical documentation, design records, version control, and deployment procedures are maintained.

8. Cost Optimisation & Vendor Management

- Evaluate technology costs, component selection, vendor capabilities, and build-versus-buy decisions.
- Improve product design for manufacturability, serviceability, and cost-effective scaling.
- Work with procurement and operations teams to identify alternative components and reduce recurring costs.
- Evaluate and manage technical partnerships, external development partners, and equipment suppliers.
- Support budgeting and resource planning for R&D;, engineering, and product deployment.

9. Business & Customer Collaboration

- Work closely with founders and leadership to align technology investments with business priorities.
- Participate in customer discussions to understand technical requirements and deployment constraints.
- Support technical proposals, feasibility assessments, product demonstrations, and solution design.
- Identify opportunities to convert customer feedback and field data into product improvements.
- Support business growth by building technology that can be replicated across multiple client locations.

Required Qualifications

- Bachelor's or Master's degree in Robotics, Mechanical Engineering, Electrical/Electronics Engineering, Computer Science, Mechatronics, or a related field.
- Typically 5+ years of relevant engineering or technology experience, with substantial experience leading multidisciplinary teams.
- Demonstrated experience in robotics, industrial automation, AI/ML, computer vision, or integrated hardware-software products.
- Proven experience taking complex technology products from development through real-world deployment.
- Strong understanding of system architecture, product engineering, testing, debugging, and reliability.
- Experience managing engineering teams, technology roadmaps, budgets, and project delivery.
- Strong decision-making, problem-solving, stakeholder management, and communication skills.

[email protected]

📌 Lead Robotics Engineer (Vadodara)
🏢 Wastefull Insights
📍 Vadodara