With the unprecedented rise in Autonomous Technologies, there is a need to accurately label different types of data to enhance the efficiency and effectiveness of AI based systems.

Chethan Sathyanarayana, our next pathbreaker, works as Data Labeling Manager at Zeitview, a firm that provides labeled data which is helpful for machine learning models to train, understand and make predictions on unseen data, for the renewable energy sector.

Chethan talks to  Shyam Krishnamurthy from The Interview Portal about his work in the development of Advanced Driver-Assistance Systems (ADAS) that helps cars accurately identify the road and make informed decisions for safe navigation.

For students, irrespective of whatever degree you pursue, focus on a domain which is evolving, develop marketable skills and keep upgrading yourself for growth.

Chethan, Your background?

I am Chethan. I was born and brought up in Karnataka, I am residing at Malur, Kolar District. I did my Bachelor’s Degree in Electronics from the National Degree College Jayanagar and Master’s of Science in Electronics with the recognition from Bangalore university. Though my initial interest was to do an MBA, due to unforeseen conditions I couldn’t do it. During my free time I play cricket which is my passion. I cook as well. There are three members in our family, my father is a civil engineer and my mother is a retired teacher. I have overall 7+ years of experience in two different domains (i.e. one in the Manufacturing industry as a quality analyst and other one is into data labeling (AI/ML)

What did you do for graduation/ post-graduation?

My only intention was to pursue a degree and then a masters which is an added advantage for my future career.

What made you choose such an offbeat and unconventional career in Data Annotation?

Initially, I got to know of an opportunity from one of my friends about an opening in data labeling. I learnt many things like effective communication, being in a team, how to handle pressure, being available when the situation demands and to be flexible and transparent during work.

I got lots of inputs from my previous leads and colleagues which helped me to grow further and now being a manager is a proud feeling.

Tell us about your career path

I initially started my career as a quality control analyst in the manufacturing industry.

I conducted rigorous quality testing and visual inspections on PVC insulated cables for households and industries. I developed and implemented efficient quality testing protocols, significantly contributing to the company’s commitment to delivering high-quality products.

I started developing an interest in the IT domain and did courses like Embedded Systems and core Java. I tried for opportunities and decided that I should grab any opportunities I get and keep moving on.

Subsequently, I entered the data labeling domain, worked on multiple projects with multiple tools and helped develop AI/ML models. I started my career in Data labelling with Cadmaxx.

Cadmaxx positions itself as an engineering‑focused IT and consulting firm, promoting itself as “Intelligence by Inheritance & Born with Experience.” It delivers services in:

  • Engineering Services
  • Staffing / Talent Placement
  • Training & Skill Development (through Cadmaxx EdTech)
  • Software Products & Digital Transformation Solutions across aerospace, automotive, embedded systems, data annotation, industrial automation, BPM, and cloud technologies

White line marking function is a feature where we do polyline annotation for the lines that exist on the road which are trained on ML models based on which automatic decisions are taken on the unseen data. Polyline annotation is labeling yellow and white lane lines on the road.

With the rise of autonomous vehicles, the demand for accurate lane line recognition has increased significantly. Lane line recognition is a crucial component of autonomous driving, as it helps the car accurately identify the road and make informed decisions for safe navigation.

Next, I worked at Anmerkung Solutions, that specializes in AI-driven automation, data analytics, and digital twin technologies, enabling smarter decision-making and operational efficiency.

Here, my role was focused on semantic segmentation. I played a key part in the development of Advanced Driver Assistance Systems (ADAS). Semantic segmentation involves the detailed annotation of images, where each pixel is assigned a specific class label. I played a pivotal role in developing Advanced Driver Assistance Systems (ADAS) by providing precise annotations, including lane and road edge annotations, meticulously outlining and defining the roadway infrastructure. I validated real-time data, significantly contributing to algorithm training for improved lane detection capabilities, ensuring accurate positioning of the annotated bounding boxes for both lanes and road edges. I led the annotation efforts for various detection types, including pedestrians, two-wheelers, and vehicles, incorporating bounding box annotations to precisely outline and identify objects. This meticulous annotation process resulted in the creation of accurate and diverse datasets, essential for the robust training of ADAS algorithms. I also supported algorithm training by providing video annotations, facilitating a comprehensive understanding of dynamic scenarios. This contribution enabled automatic decision-making within the object detection domain, enhancing the system’s ability to recognize and respond to various objects and scenarios in real-time.

After my above stint, I joined Continental. Continental is a global product-based company and the competitor for Bosch. They manufacture continental tires and as well have an IT firm which is specifically into the automotive domain. My role was Senior Annotation Engineer.

At Continental, I led the generation of precise ground truth data for facial landmark positions, ensuring accuracy for critical ADAS features collaborated with cross-functional teams to define and annotate eye landmarks (Inner/External corner) with a focus on optimizing driver monitoring systems. I ensured the success of the visibility task by meticulously annotating eye landmarks, sub-nasal point, and mouth corner points, contributing to enhanced driver safety features. The facial landmark detector is crucial to fatigue driving recognition.

Now as we all know AI is the trending domain and market globally, I am on the right track and need to upgrade to survive in this domain.

How did you get your first break?

I was looking out for a break and kept applying for roles related to my qualification. I got a word of mouth reference from my friend who did AutoCad and other courses at Cadmaxx. I applied for an open position and got selected for the role of Trainee Engineer.

What were the challenges you faced? How did you address them?

Challenge 1: Handling pressure where the tasks are overloaded. Be patient and give your best to finish it.

Challenge 2: In a team we have people from diverse backgrounds, and so we need to bring them all towards a common goal. We need to make them understand the impact of the work. If there is no unity, understanding and coordination between colleagues, the work will suffer.

Where do you work now?

Currently I work at Zeit view as Manager, Data labeling. We provide labeled data which is helpful for the machine learning models to train and understand and make predictions on the unseen data. We provide services in the renewable energy sector with five verticals. (solar, wind, telecom, properties and construction monitoring)

Zeit view captures data by using drone and aircraft to do inspections on verticals such as wind, solar, properties, telecom and construction monitoring. We perform labeling on wind turbines, solar panels (IR and RGB panels), commercial and residential rooftop, telecom and construction monitoring sites. From these labeled data, ML models identify defects which come across all these verticals and give results which reduces manual efforts.

What are the skills required for your role? How did you acquire them?

This work has a minimum graduation requirement; one needs to understand software tools which are related to the domain for data inspection.

Deadlines are always tight, and the approach we bring to complete the task is always challenging.

Renewable energy is a sector where we serve nature by inspecting different energy sources to avoid natural disasters. I am happy to be part of this domain.

How does your work benefit society?

My work contributes to enhancing energy access, enabling community empowerment and protecting the environment, thus mitigating climate change, which results in cleaner air and improved public health.

Tell us an example of a specific memorable work you did that is very close to you!

We got a deadline to finish a task overnight and deliver it by next day. I was worried whether it would be possible to finish it or not. My colleague was involved along with me to support my deliverables and we delivered on time.

Your advice to students based on your experience?

Try to pursue a degree based on your interests and not stick to a domain where you feel like you can handle it, have enough skills and keep upgrading your skills for growth.

Future Plans?

I am looking forward to learning scrum or project management skills and moving on.