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Fiddler Team

Our Fiddler Family Has Grown!

Fiddler is Growing!

It’s been an exciting and rewarding journey these last two and a half years at Fiddler. And I’m excited to see the continued growth of our Fiddler family. The common thread amongst our team is the passion for building responsible AI technology (and having fun while doing it!) and this thread continues in our newest team members. The need for Model Performance Management to build Responsible AI is stronger than ever and I’m honored to welcome this newest cohort of Fiddlers to our team – a very warm welcome to all of them! 

Go-To-Market Team

Timir Naik, Head of Customer Success

Before joining Fiddler Labs, Timir led the Customer Experience Team for Americas at AppDynamics for 2 years. Prior to AppDynamics, he was a VP at Deutsche Bank where he led several regulatory, compliance, business architecture and technology governance global programs. He is passionate about technology and business value provided by the disruptive technologies that surfaced over the recent years.  Outside of work, he likes to spend time with his family, exotic vacations and reading.  Timir strongly believes in our mission to unlock the AI black box:

We live in a data-driven world, where users expect results, but don’t want to compromise on human rights.  The world has adopted AI for everyday decision making by suggesting, “what to add to your shopping cart?” to “are you approved for a credit line increase?”.  In this new world it is imperative as a customer we understand the rationale behind why certain decisions are made.  Being a technologist, I would like to be able to be part of an organization that will empower companies with the right tools to peel open the AI black box and mitigate any reputational risk, unwanted bias and efficiently run their business with trust in AI.

Henry Lim, Sr. Product Marketing Manager

Henry comes from a diverse marketing background – customer research, account executive, brand marketing, and product marketing. Prior to joining Fiddler, Henry was a product marketer at Ople.ai for two years, after finishing his MBA at the University of Virginia Darden School of Business. He is passionate about AI and enabling teams to build better AI solutions.

Throughout my career, I learned that data is everywhere and not many companies are utilizing it properly. Then I came across big data analytics, machine learning, and data science. I immediately realized that advanced analytics will become essential in every company’s growth, so I started to venture into the AI industry as a product marketer. Previously at Ople.ai, I helped companies realize the importance of AI and how to quickly get started with predictive analytics. At the same time, I learned that building a model is just the beginning; maintaining models in production is a whole other story. That’s why I’m super excited about Fiddler. Fiddler is empowering companies to do more with their ML models with superb monitoring solutions with built-in explainable AI to build reliable and accountable AI systems.

Engineering & Data Science Team

Seema Shet, Data Scientist

Seema joins us from UC Berkeley where she completed her Masters in Statistics. Before joining Fiddler, she worked in the analytics divisions of HSBC, Ola Cabs and Citi.

I feel like I have been living under a rock or maybe a really big black box! My eye-opener was the Pattern Classification course from UCB in my last semester where our Professor talked about Fairness in ML. What surprised me most was the lack of talk on the explainability/interpretability of the ML models (or maybe it was just me who wasn’t aware of it). Why aren’t people talking about it more often? Why are people not aware of it when this can have a huge impact on their lives? Why isn’t it regulated for every sector? These were just some of the questions that came to my mind. I think Fiddler is doing a really good job in bridging the gap between wanting to use ML but also using it responsibly and I’m excited to be a part of this!

Sarmed Chaudhry, Software Engineer

Sarmed graduated from UCSD with a B.S. degree in Computer Science.  Prior to Fiddler, he  worked at a cybersecurity startup, Armorblox where he  was part of the team that was instrumental in building the alpha and beta versions of the product UI. 


Growing up in the bay area, I have witnessed the rapid rise of the tech industry, especially with AI, and how this growth also caused concern with the very ethics of AI in and of itself.  I now join Fiddler to provide my front end experience to build the bridge towards responsible and explainable AI through the means of improving user interactivity and experience. Helping businesses to trust and understand AI is the motivation that brought me to where I am today. I am excited to be a part of a company which is on its way to being a leader in providing solutions to the everyday concerns of AI.

Kai Rawal, Machine Learning Engineer

Kai comes from Harvard University with an M.S. degree in Data Science and a research background in interpretable machine learning. 

“With my research background in interpretable machine learning, Fiddler’s model monitoring and XAI offerings obviously resonate deeply with my personal interests. More broadly, I am optimistic about technology and interested in contributing to its increased adoption as a source of good in the world. Specifically, with AI, this implies the need to build trustworthy, fair, and transparent models. To me, Fiddler’s most interesting impact is the ability to empower every data scientist with the latest tools and techniques to build trust in their models, thus augmenting their abilities.

Technological advancement and sophistication have often historically been accompanied by the centralization of technical resources and capabilities. As a relatively young field, this is likely to be the natural course for artificial intelligence too – where the ability to effectively deploy and debug models, and engender trust in them, get concentrated rather than democratized. Fiddler mitigates this issue brilliantly by bringing cutting-edge model interpretability techniques into production and making them easy to use for everybody. As the machine learning engineer on Fiddler’s team, I’m looking forward to contributing to this mission. I am also incredibly excited to work with so many experienced and talented people in a focussed and driven environment.”

We are still growing so if you are interested in joining us, head over to our Careers page and apply!

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