About the Company

Wastefull Insights is a robotics and AI company focused on developing intelligent automation solutions for waste segregation and material identification. The company integrates robotics, computer vision, AI, mechanical systems, and industrial automation to build technology solutions for real-world operational environments.

Role Overview

We are looking for an experienced and hands-on Chief Technology Officer (CTO) to lead the company's overall technology strategy, engineering teams, product development, and technology deployment.

The CTO will be responsible for converting business requirements into scalable, reliable, and commercially viable technology solutions. This role requires solid technical expertise across robotics, AI/ML, computer vision, embedded systems, mechanical engineering, and industrial automation, along with the ability to lead cross-functional teams and deliver projects from concept to deployment.

The ideal candidate should be capable of making critical technology decisions, building robust engineering processes, improving product performance, and aligning technology development with the company's business objectives.

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 on-site 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 10+ 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]

📌 Chief Technology Officer (Vadodara)
🏢 Wastefull Insights
📍 Vadodara