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Powering Through Pixels: The Role of Software Engineer Dananjayan Thirumalai in Shaping Online Selling Platforms

Posted on the 12 August 2024 by Jyoti92 @Jyoti_Chauhan1

In online commerce, speed and efficiency combined with cutting-edge tech and the application of Artificial Intelligence drive success.

At the forefront of this billion-dollar industry is Dananjayan Thirumalai who has worked at two market leaders, Amazon and DoorDash.

Dananjayan Thirumalai

Dananjayan, now recognized as a pioneering force in the tech industry, has played a pivotal role in transforming online selling platforms through his expertise in machine learning, Artificial Intelligence, and scalable systems.

His work has set new standards for how digital marketplaces operate, ensuring they are faster, smarter, and more efficient—wins for companies and their customers.

Currently, the Lead Software Engineer at the online delivery platform Doordash says he is motivated by the impact of his work: “Understanding that my work contributes to delivering food and essential items to individuals in need, including those with disabilities, is truly fulfilling,” reveals Dananjayan.

“End customers want a 100% batch rate, meaning the same dasher delivers both orders in a bundling scenario. They also want their favorite stores to be recommended consistently.

“That is why I have made it my mission to find the perfect balance of customer needs, dasher availability, and DoorDash optimization. What has made us able to improve these aspects is using machine learning and metrics like attach rate to make our service as superior and successful as possible. “

Dananjayan’s journey in software engineering stretches from university in India to his current job in Seattle. His passion for technology and innovation grew early, driving him to develop solutions that meet and exceed modern e-commerce demands.

Dananjayan earned a computer science degree in India in 2009 and a Master’s in computer science at Arizona State University in 2012.

Later that year, he started his career at Amazon, working on identifying and pushing its sponsored products.

His tenure at the online marketplace marked a significant milestone in his career. At one of the world’s largest e-commerce platforms, he was instrumental in developing scalable systems capable of handling millions of transactions daily: “Scalability and reliability are crucial for any online platform,” he says.

“We needed systems that could perform under immense pressure and provide a seamless user experience.”

At sponsored products, he led the analytics and reporting team, responsible for ingesting millions of live clicks and impressions, processing them for a fast channel of advertiser budgeting and a reliable channel of real-time and offline reports, advertiser billing, analytics, and figuring out estimated CTR used for Machine Learning (ML) based prediction of Ads and providing insights on how customers interact.

At the core of Dananjayan’s innovations lies the strategic use of Artificial Intelligence (AI) and ML: “These technologies are game changers in how we approach online selling,” he asserts.

“By analyzing vast amounts of data, machine learning algorithms can predict customer preferences, optimize product recommendations, and enhance search functionalities.”

Another significant project led by Dananjayan was the development of AI-driven recommendation systems. This initiative used machine learning techniques like Bayesian models and deep neural networks to predict the recommended items.

Traditionally, collaborative filtering techniques such as “people who bought this also bought this’ ‘ were used before: “Our goal was to boost high conversions while enhancing the shopping experience by presenting customers with relevant product suggestions,” he says.

This innovation increased Amazon’s overall revenue and improved customer satisfaction by making their shopping journey more personalized and intuitive.

He then moved on to work on improving the accuracy of its Alexa voice recognition system. The ASR (automatic speech recognition) models are frequently created, and the benchmarking process is speeded up by 97%.

Dananjayan took those skills to DoorDash in 2019, where he has had a technical lead role, and has been a founder member of Dashpass, Group Orders and DoubleDash.

He remains a staff engineer to this day: “DoorDash provided a unique opportunity to apply my skills in a dynamic and fast-paced environment,” he recalls.

He takes his role so seriously that at least once a month, he’ll do a DoorDash delivery himself, called a dasher, to experience firsthand how the system works.

“It’s important to know what the experience is for the customer so you can improve on it. I also keep learning and integrating new ML approaches like large language models and deep learning. I want to use these advancements to provide even better customer experiences,” he says.

To this end, Dananjayan’s approach involves leveraging AI and machine learning to create systems that anticipate customer needs, streamline operations, and boost overall efficiency.

At DoorDash, Dananjayan focused on optimizing delivery routes, ensuring timely deliveries, and enhancing the overall customer experience.

One of his major contributions was the introduction of the bundling system. This ML-driven feature allows customers to receive multiple orders from different stores in a single delivery: “The bundling system uses machine learning to optimize delivery routes, reducing wait times and increasing efficiency,” Dananjayan explains.

“This innovation benefits both customers, who enjoy faster deliveries, and dashers, who can maximize their earnings by handling multiple orders at once. My own family uses it, which I am very proud of.”

His standout achievement was transforming its monolithic architecture into a more flexible microservices framework. This shift allowed DoorDash to manage its vast array of services more efficiently: “Moving to microservices enabled us to isolate and address issues quickly, deploy updates seamlessly, and scale individual components based on demand,” Dananjayan explains.

It involved extracting several highly important databases, and critical Tier-0 services which are integral for every request to DoorDash ecosystem: “I worked on making services for consumer profiles – for maintaining critical consumer data like customer’s default address,” says Dananjayan.

Another important service is managing Dashpass, DoorDash’s superpower subscription program, which provides many benefits to customers: “It includes a free delivery fee and a reduced fee for service,” says Dananjayan.

“That makes it a win-win for everyone involved. These services handle huge traffic – Imagine more than 50,000 requests per second that should be handled at less than 50 milliseconds!

“The difference I make for the end customer keeps me motivated. I also love the challenges I deal with daily. They can allow me to dive in, figure out solutions, weigh the pros and cons, and learn from people I work with who are intelligent and great problem solvers. Plus, I enjoy owning projects from start to finish, like I’m the CEO of my team. It enables me to take ownership of the whole process.”

Integrating AI and ML into online platforms comes with its own set of challenges. Dananjayan highlights the importance of high-quality data and robust models: “The success of any AI system depends on the quality of data it is trained on,” he emphasizes.

“Ensuring data is accurate and representative is crucial for making reliable predictions and decisions And complementing them with error correction techniques.”

Dananjayan employs rigorous testing, monitoring, and continuous improvement to overcome these challenges: “We constantly evaluate our models against real-world data and make necessary adjustments to improve performance and increase the speed of feedback loop for faster learning,” he explains. This approach ensures the systems remain reliable and effective even as they scale.

Rohit Raghunathan is Head of Engineering at New Verticals Consumer Organization at DoorDash and Dananjayan’s direct manager.

He says: “If you give him a problem, he runs with it and takes ownership, which is often needed to solve complex engineering problems. Dananjayan has a superior level of insight and empathy.”

Speaking directly of Dananjayan’s expertise at DoorDash he reveals: “He was the tech lead for the DoubleDash product, and in that, he had to drive what is called the post-checkout experience, which is one of the harder parts of that product.

“The fact that he could build relationships with partner teams, understand the data deeply, and leverage his machine learning skills was critical.

He has a master’s in computer science focussed on data mining and ML from Arizona State University, so he brings that knowledge to the fore.

“In the post-checkout project, he could leverage his machine learning skills to figure out when exactly in the lifecycle of an order to fire certain product experiences. That was a critical piece for the overall success of DoubleDash.”

Rohit also cites the work Dananjayan did at the company during the company as vital to its success: “It ended up helping society by keeping the DoorDash service available, which was crucial during that time.

“His intuition around what to build for consumers is excellent. He can interact with customers, understand their pain points, and translate that into products to build.

“With the advent of Gen AI, Dananjayan’s experience building machine learning-based products and large-scale engineering systems positions him well to benefit US companies and society.”

Looking to the rapid changes ahead, Dananjayan envisions even greater AI and machine learning integration in online selling platforms:  “The future is about creating intelligent systems that can adapt and evolve,” he says.

He sees potential in using large language models and real-time data analytics to enhance these platforms’ efficiency and responsiveness: “By making logistics operations more environmentally friendly, AI can contribute to broader sustainability goals while maintaining high levels of service quality.

“In the future, automated delivery could be a game changer, with food being delivered on automatic small battery cars or drones, which could help our carbon footprint.”

Beyond his technical contributions, Dananjayan is passionate about mentoring the next generation of engineers and data scientists: “I work with three or four engineers a year, enabling them to improve their skills. Mentoring is incredibly important to me,” he says. “I want to help others develop their skills and achieve their potential.”

Dananjayan’s work on sponsored products and personalized at Amazon and Group Orders, DoubleDash and DashPass at DoorDash exemplifies the real-world impact of his innovations. By leveraging machine learning, he has transformed how these platforms interact with users, making their experiences more engaging and relevant.

“I aim to keep learning and integrating new technologies like machine learning and large language models to improve our services. I want to use these advancements to provide even better customer experiences,” he says.

“I also want to be remembered as technically strong, capable of solving the most complex problems in distributed systems and machine learning, as well as a great and empathetic coworker.”

Dananjayan’s journey is a testament to the power of innovation and the impact of dedicated engineering. His ability to blend technical expertise with a deep understanding of customer needs has made him a standout figure in the field. As the digital landscape evolves, Dananjayan remains at the forefront, shaping the future of online selling for all of us.


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