Life does come a full circle when you begin your career as a microprocessor technologist at Intel and don the technologist hat once again as Research Fellow at Nasa, but only after dabbling in diverse roles in technology (Product Management, Sales/Marketing, Strategy) including a successful exit as the Co-Founder of an analytics startup !

Raj Pai, our next pathbreaker, works on research and development of data and AI/ML application software and hardware in NASA’s Aviation Systems Division, a world leader in air traffic management (ATM) research.

Raj talks to  Shyam Krishnamurthy  from The Interview Portal about not having a pre-laid out plan but making it his personal goal to go along with technology trends, see all facets of the business of technology, from being an engineer in R&D, to product management, product marketing, sales and marketing, and then running his company, in the process bringing all his diverse experiences in technology innovation to aerospace. 

For students, there are no successes and failures in a career, it’s all about the experiences that help you understand what you personally enjoy doing by trying out different roles.

Raj, tell us about your background?

I grew up in a family full of bankers, and right from high school I was intrigued by what an engineer does. I dabbled in building some simple projects in high school, like a transistor radio and a music system (those days it was hard to get all components). These further fueled my interest, and I took up Electronics in college, and appeared for JEE. Most of my journey to IIT was driven by personal drive, help from friends, a lot of motivation from family, and perseverance to keep learning.  

What did you do for graduation/post graduation?

At IIT, I took up Electrical Engineering, classes were broad based across signal processing, machines, circuits, lots of math. My focus for my BTech research project was analysis of speech waveforms and speech synthesis. For my Masters’ (Electrical & Electronics Engg), I moved to the US, where I was delighted to have access to a clean room for designing and fabricating solid-state biomedical sensors. After graduation, I was recruited at Intel to join their Design Technology group where microprocessor designs were just breaking the 66 MHz CPU speed barrier (yes, this was early 90s). As a young engineer, in the industry’s leading semiconductor firm, I was excited to be at Intel and made incredible lifelong friendships and had superb mentors. 

Tell us about your career path

Looking back at my career, I definitely did not have a pre-laid out plan. I went from hardware and chip design at Intel to enterprise software and big data/analytics and later to analytics/AI/ML applications. My career choices were driven by a strong interest to keep learning and evolving as the tech industry kept evolving. The era of PC, client-server computing drove the internet/telecom industry, which then evolved into big data/AI/ML with cloud deployments. Each one of these were big shifts and I had to learn new things which made it exciting. Along with the technology trends, it was my personal goal to see all facets of the business of technology. From being an engineer in R&D, to product management, product marketing, sales and marketing, and then running my company, gave me invaluable experience. Lessons learned in building and mentoring teams, working in and across functional groups, going from cradle-to-grave in product-life cycles, partnering and selling tactics and strategies, were priceless. There were successes and failures, but all the experiences helped me understand what I personally enjoyed doing by experiencing and trying different roles.

After this journey, I decided at my core, I was a creator and technologist, which led me to my current position as ‘Research Fellow” at NASA.

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

As I transitioned through different functional roles and different industries, some hurdles I had to work through included

  • Being accepted as someone from outside the domain or functional area (eg. Engineer moving to become a PM, learning about energy industry or learning about aerospace in my current role)
  • Different working culture in companies
  • Different pace of execution at startups vs. mature companies 
  • Learning new technology domains 

Let me start with the easiest. Learning new domains took time, patience and a personal curiosity. For people, culture, and acceptance, I had to be patient to learn from others (having personal mentors helps a lot) and constantly keep adapting and applying what I learned. For folks starting in their career or even in the middle of career changes, I would highly recommend being diligent about meeting and talking to people in the industry, and using informational interviews to learn and gauge when planning a career change. You will be surprised how helpful and generous are with their time to help others. 

How did you land the job at NASA, having a very different background from a typical NASA profile?

I was exploring what next for the second big phase of my career and wanted to do something which would align with my technology interests as well as get the opportunity to learn and contribute in a new industry. As I mentioned above, I spoke to a number of friends, mentors, acquaintances in many industries, startups, large companies, leaders in their respective domains. I have never worked in government and specifically in aerospace. I had multiple discussions with people I would be working with (for almost a year) and found alignment in research, role, and team, and decided to join the incredible team at NASA in Ames Research Center. 

Tell us about your current role at NASA

At NASA, I work on research and development of data and AI/ML application software and hardware in NASA’s Aviation Systems Division, a world leader in air traffic management (ATM) research. I design and coordinate innovation programs for air traffic systems to drive safety and efficiency for complex air transportation operations including managing new airspace entrants (like unmanned drones) mixed with traditional traffic. My areas of research include overall architecture and design choices, including identifying and integrating appropriate communication and data systems and analysis/predictive tools (including artificial intelligence sub-systems), deployed on advanced ground and mobile embedded hardware systems. 

What do you love about this role?

I serve as Data Fellow at NASA Ames Research Center.

I love this role as I get to serve as a technical and subject matter expert for big data, service-oriented architecture, autonomy, and AI/machine learning for agency management, other government agencies, and the industry. I also get to bring my previous career experience in technology innovation to aerospace. 

How does your work benefit society? 

My research work in applied AI/ML has direct world implications in our airspace building on the safety and efficiency for general and commercial aviation. As we look ahead, the early concepts I am building/proposing for data-driven software and hardware systems, in particular with voice-based communication with operators in the loop, will hopefully have impact for decades as autonomous flight and operations enter the global airspace. Excited to see how the future evolves. 

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

My current ongoing work in NLP (Natural Language Processing) at NASA, winning the Amazon Web Services Startup Challenge while working on my gaming analytics startup (Claritics), and launching a new product for data lineage analysis for our enterprise customers in healthcare, financial verticals at Informatica.

Your advice to students based on your experience?

Be curious, keep learning and growing, and build strong authentic relationships with colleagues, mentors, bosses at every stage of your career.

Future Plans?

Exploring and learning how education will evolve in the future and how education will adapt and evolve to bridge inequities in our society across geographies, races, genders, economic status, and future trends.