Amey Dharwadker, AI Engineering Manager at Meta and winner of BCS Search Professional of the Year 2023, shares insights from his career with Grant Powell MBCS.
Amey Dharwadker, winner of the BCS Search Professional of the Year award in 2023 Presented by the BCS Information Retrieval Specialist Group, has undertaken a varied and successful career which has seen him excel in a variety of prestigious tech roles, is currently working as an AI Engineering Manager at Meta. Here Amey shares his professional journey and achievements, his thoughts on AI, its impact on digital search capabilities and where it will take us, and his tips and guidance for those entering the industry.
How did it feel to be awarded BCS Search Professional of the Year 2023?
Receiving the esteemed BCS Search Professional of the Year 2023 award was a moment of immense honour and pride for me. The rigorous evaluation process, culminating in being chosen as the winner from a pool of top search and information retrieval professionals globally, was truly gratifying. The recognition underscores the impact of my contributions to advancing state of the art innovations, products and services in the field on a global scale. Being honoured with such a prestigious accolade early in my career serves as great encouragement to continue striving for excellence, pushing the boundaries of innovation and shaping the future of technology.
Can you summarise your career up to your current role?
Driven by my passion for mathematics and physics, I completed my bachelor's degree in Electronics and Communication Engineering at the National Institute of Technology Tiruchirappalli in India. During my undergraduate studies, I became fascinated with machine learning and computer vision through elective courses. After graduation, I worked at Analog Devices in Bengaluru, India for two years, contributing to Level 2 partial driving automation by developing computer vision based advanced driver assistance systems (ADAS). I then moved to the US to pursue a master’s degree at Columbia University in New York, specialising in computer vision and machine learning. I joined Meta full time in 2015 on the Facebook news feed ranking team, developing personalised video and link recommendation ranking models.
My work played a pivotal role in transforming daily content discovery and engagement for billions of users worldwide, dramatically enhancing user connections and engagement. In 2018, I led innovations in Facebook Ads’ ranking that substantially increased clicks, conversions and revenue across Facebook’s family of apps. Since 2019, I have worked on Facebook's video recommendation products. As a machine learning technical leader on the video recommendations ranking team, I significantly improved Facebook’s watch and reels recommender systems, positively impacting over 2 billion daily users.
My work building and improving these large scale recommendation systems played a crucial role in making our video products immensely popular — now accounting for over half of all time spent on Facebook! I currently lead the Facebook video recommendations ranking team as an AI Engineering Manager at Meta. My team connects people worldwide to high quality, personalised video content relevant to their interests across Facebook's video products.
What have been some of your greatest career achievements so far?
Throughout my career, I have had the privilege of collaborating with exceptional engineers and researchers to tackle large scale, complex, real world challenges, making each day a valuable learning experience. My contributions at Meta — particularly in advancing user recommendations — stand out as pivotal achievements, garnering recognition through research publications, patents and positive global media coverage. In addition, as a co-organiser of the VideoRecsys Workshop at the ACM Recommender Systems Conference, I’ve facilitated a platform connecting researchers, practitioners and industry experts, igniting fruitful discussions on video recommendation trends and challenges, thereby catalysing innovation in this rapidly evolving space. I've been privileged to share insights at renowned AI and ML conferences worldwide, addressing diverse audiences on topics spanning large language models, deep learning, recommender systems design and bias mitigation.
These speaking engagements facilitated meaningful connections with mentors and mentees, enriching my professional journey. Being able to impart knowledge and to mentor aspiring ML engineers and scientists brings me immense satisfaction as I witness the positive impact of fostering growth and empowering the next generation of tech innovators. The formal recognition I have gained, such as the IET India Youth Engineering Icon of the Year Award, Scientist of the Year Award and Most Prominent Industry Expert Of The Year In Machine Learning, underscores the societal impact and technical excellence inherent in my work.
These honours validate not only my individual achievements but also the collective efforts of the talented teams I've had the privilege to lead and collaborate with. In essence, my most significant career achievements have been about leveraging applied research, engineering innovations and thought leadership to positively impact billions of lives and shape the future trajectory of user personalisation. I remain deeply grateful for the opportunities to collaborate with brilliant minds and drive meaningful change in the ever evolving landscape of technology and AI.
How has AI changed the world of online search? What opportunities does AI present, and also what challenges does it bring?
AI has fundamentally transformed online search from keyword matching to understanding user intent and context. This enables more personalised, efficient and intuitive recommendations. Search engines can now understand user queries better by using techniques like natural language processing and machine learning, leading to more accurate and relevant results. AI powered recommendation systems further enhance user experience by suggesting content tailored to individual preferences, driving engagement and satisfaction. The opportunities presented by AI in online search are vast. It enables deeper insights into user behaviour and preferences, allowing for more targeted content delivery.
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Additionally, AI can automate various aspects of search engine optimisation, helping businesses reach their target audience more effectively. However, AI also brings challenges, including concerns about bias and algorithmic fairness. As AI algorithms increasingly shape the content users see, ensuring transparency and accountability in decision making processes becomes paramount. Additionally, this reliance on AI raises questions about data privacy and security, requiring robust measures to protect user information while delivering personalised experiences. Mitigating these challenges whilst harnessing the immense potential of AI to create a more inclusive and equitable information landscape is essential.
As a search professional, what are some of the key skills required for people who are interested in a career in this area?
A career in search technology demands a unique blend of machine learning and AI domain knowledge, software systems skills, creative problem solving and an intrinsic drive to innovate. At the foundation, one must intimately understand the problem space — what is the user’s true goal when they search? Can you intuit patterns in data and quantify success beyond accuracy metrics? This needs to be complemented by strong software engineering skills for building robust, scalable search systems and infrastructure. Search and recommender systems are rarely solitary components. Grasping how your work fits within a broader ecosystem, from data pipelines to downstream products, is critical for delivering impactful, production ready solutions. Beyond technical skills, an innovative mindset helps drive advancements through tackling open ended problems. Remember, exceptional engineers stand out with their resourcefulness and adaptability, and its important to embrace continuous learning in this fast evolving domain.
With AI-powered algorithms now able to analyse user behaviour and search patterns – what developments do you think we can expect to see in the near future?
In the near future, AI-powered algorithms will continue to drive innovations in personalised content delivery and user experience refinement. One exciting development is that advancements in natural language understanding will enable more conversational search interactions, where users can engage with search engines using natural language queries and receive contextually relevant responses. This shift towards more intuitive and conversational interfaces will democratise access to information, making search more accessible to users with varying levels of digital literacy. Moreover, AI powered analysis of user behaviour and search patterns is leading us towards a future of proactive information discovery; imagine a search engine that anticipates your needs based on your past interactions, surfacing relevant information before you even explicitly search for it. This could be particularly transformative in areas like education, where content tailored to individual learning styles can be automatically presented.
You can find out more about Amey at his website and LinkedIn
