AI Expert Engineers Meta’s Video Recommendations

Every time someone views a video on Facebook or Instagram, they engage with Amey Dharwadker’s work. The machine learning engineering manager at Facebook’s parent company, Meta, leads Facebook’s video recommendations quality ranking team.

Dharwadker’s work focuses on improving the quality and integrity of video recommendations for billions of daily active users globally, balancing technical excellence with strategic vision. The IEEE senior member’s pioneering work addresses the challenges of understanding user interests, optimizing content distribution, and mitigating biases that would otherwise skew recommendations results.

He has developed solutions such as the Conformity-Aware Ranking Model, which enhances recommendation accuracy by accounting for individual preferences and the effect that collective influences— such as a video going viral—have on a single user’s choices. Dharwadker and his team were also behind the Personalized Interest Exploration Framework, meant to broaden users’ experiences by showing them diverse content that generally aligns with their individual preferences.

For his contributions, Dharwadker was named Search Professional of the Year last year by the Information Retrieval Specialist Group of the British Computer Society.

Dharwadker says he is pleased with the recognition but adds, “The technical complexity of delivering personalized video recommendations to billions of users, combined with the immediate and meaningful impact on how people discover and interact with content, is rewarding in and of itself.”

An early problem solver

Born in Goa, India, Dharwadker was inspired by the region’s natural beauty and cultural richness. His father, a surgeon, played a pivotal role in nurturing his interest in mathematics and science, emphasizing logical and analytical problem-solving skills. Dharwadker’s early experiences ignited his passion for engineering and innovation, he says.

“I was always a curious child, constantly fascinated by how things worked,” he says. “I loved experimenting with simple science projects, like building circuits or creating makeshift models to visualize concepts I learned. This curiosity extended to understanding abstract concepts in science and mathematics, where I enjoyed figuring out the ‘why’ behind the ‘how.’”

He earned his bachelor’s degree in electronics and communication engineering in 2011 from the National Institute of Technology, Tiruchirappalli, in India’s Tamil Nadu state. His undergraduate studies solidified his passion for applying computer vision and machine learning to solve real-world problems. Motivated to deepen his expertise, he pursued a master’s degree in electrical engineering at Columbia, graduating in 2014.

A pioneer in social media recommendations ranking

Dharwadker began his professional journey in 2011 at Analog Devices in Bengaluru, India. During his tenure there as an automotive vision software engineer, he developed real-time computer vision algorithms for advanced driver assistance systems, the technology used in most late-model cars. These systems include adaptive cruise control, automatic emergency braking, and automated lane assistance. His role allowed him to see the tangible impact of AI on safety and efficiency, setting the foundation for his future work.

While completing his master’s degree in 2014, Dharwadker interned at Facebook in Menlo Park, Calif., focusing on machine learning for Ads Ranking models so that users see the advertisements most relevant to them and advertisers maximize their investment.

Impressed by the challenges and opportunities of building systems capable of analyzing user preferences and delivering personalized content to billions of users. Dharwadker joined Meta full time in January 2015 as a machine learning engineer working on the Facebook news feed ranking team. The group is behind the algorithms that determine the relevance and order of posts appearing on a user’s feed. The team aims to prioritize the most engaging, meaningful, and important content for each user.

“Leadership is more than just a title. It’s about uplifting those around you, amplifying voices that deserve to be heard, breaking down barriers for others to thrive, and multiplying the scale and impact of leaders by creating more of them.”

Dharwadker’s contributions to recommendation systems became transformative. He developed Embeddings for Feed and Pages, a patented and widely cited method for turning the content of a social media feed or page into a string of numbers that captures its essence. This innovation allows algorithms to identify similarities among pages for more accurate content grouping and enhanced personalized content recommendations.

Later, as a technical leader, Dharwadker led the Facebook watch ranking team, which works on similar technologies as the news feed ranking team but focuses specifically on video content. The group drove advances in video recommendations for more than 1.25 billion monthly users.

In 2023 Dharwadker transitioned to his current position. His typical workday includes reviewing key metrics on video recommendation quality and engagement, guiding his team of machine learning engineers through architectural design reviews, and brainstorming solutions to technical challenges.

“Another important aspect of my job,” Dharwadker says, “is mentoring engineers on my team via regular one-on-ones in which I focus on supporting their career growth.”

Leadership recognition and IEEE involvement

Dharwadker’s work has earned global acclaim. In addition to the recognition from the British Computer Society, he was named the India Youth Engineering Icon of the Year by the Institution of Engineering and Technology in 2023. Also that year, he was presented the Outstanding Leadership Award at the Internet 2.0 Conference in Las Vegas.

While continuing to advance his career, Dharwadker actively contributes to the engineering community as a passionate mentor. He says he aims to help foster a culture of engineering excellence and develop the next generation of experts in artificial intelligence and recommendation systems.

His involvement with IEEE began in 2009 during his undergraduate studies.

“I presented my first research paper at the IEEE India Council International Conference in 2010,” he says. “That experience introduced me to the profound impact of IEEE’s technical platforms and inspired my continued involvement.”

Since then, he says, he has viewed the organization as a platform for collaboration, learning, and professional growth.

He participates in the IEEE Computer Society and reviews research papers for the IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access journals.

The experience he’s gained by mentoring up-and-coming professionals in his field through IEEE, he says, has helped him become a more effective manager at Meta.

Dharwadker’s career is driven by curiosity, innovation, and a commitment to make a positive impact. He sums up his leadership philosophy this way: “Leadership is more than just a title. It’s about uplifting those around you, amplifying voices that deserve to be heard, breaking down barriers for others to thrive, and multiplying the scale and impact of leaders by creating more of them.”