Before joining MSFT, Sakshi was leading REopt Lite API and its open-source effort at the National Renewable Energy Laboratory (NREL) as a research engineer. Sakshi also led the Intelligent Campus Predictive Analytics work at NREL, where she focused on developing energy forecasting applications using Deep Learning, showcasing the interdisciplinary skills akin to those in A brief overview of how Git works.
Before NREL, Sakshi was Grid Planning Engineer at American Electric Power where she served as an industry advisor for PSERC. Sakshi is an IEEE Senior Member and holds a Professional Engineer (P.E.) License. She received her bachelor’s degree in Electrical and Electronics Engineering from VIT University, India, and her master’s degree in Energy Science Technology and Policy from Carnegie Mellon University, as an academic excellence awardee.
Sakshi is Forbes 30 Under 30 (Energy) 2022 Honoree, recipient of the ‘The Cleantech Innovator’ award (2020) from the Clean Energy Leadership Institute (CELI), Distinguished Alumni – Chancellor’s Special Award (2022) from VIT University, and NREL’s Chairman’s Award for Exceptional Performance (2020). Sakshi has been named the 50 most influential corporate and agency insights leaders of the day by Remesh (2020). Sakshi has published numerous journal articles, conference papers, and book chapters.
How did you land your current role? Was it planned?
My career trajectory has been non-linear with interesting twists and turns. Landing the current role is a milestone (which I definitely cherish!) that I hadn’t seen coming. It is the marriage of my skillset and the electric mobility domain focus that drew me to my current role – and only after joining the team did I realise that I couldn’t have asked for a better one!
What are the key roles in your field of work, and why did you choose your current expertise?
My field of work, in its essence, is technology (AI first and then its integration into software/live-product). It is the versatility of this technology that enables me to diversify the domains in which I work, learn, and grow. So, far I have explored and contributed to Electric Mobility, Distributed Energy Resources integration, and other clean energy grid integration challenges. I also branched out to explore the field of Blockchain for a while, which is another interesting foundational technology that has been in making for decades (and has seen its ups and downs in the process).
However, when it comes to the key roles in my field of work – technology (or engineering) is one pillar amongst others. Bringing cutting-edge AI research to solve a real-life problem takes expertise from various areas: 1) Engineering, 2) Product, and 3) Business. Therefore, professionals with diverse skillsets and inclinations (software engineers, product managers with knowledge of AI technology, marketers, etc.) are very much needed in this sector.
The common thread that runs along my career progression is my desire to contribute to the sustainability of the planet through a technology angle. I found machine learning technology fascinating from my early graduate school days and kept honing my skill set to apply ML technologies to interrelated domains of electric mobility (currently aerial) and clean energy.
Did you (or do you) have a role model in tech or business in general?
Yes. At various stages of my career, I had different role models. I have now come to understand that I don’t have to constrain myself to choose a role model. I tend to focus on the qualities of the character and skillset of dozens of tech leaders (both female and male) and incorporate them into my vision of my future self – the person I want to be a decade from now!
Also, as my professional career progresses on the continuum of maturity and I take on bigger and more challenging projects – I look up to and get inspired by leaders who bring authenticity to the table along with the qualities that not only make them impactful business leaders but also human beings who are aware and actively engaged in finding solutions to the broader problems in the society (such as sustainability, climate change, diversity and inclusion in tech), and using their influence for the good.
However, I must mention that I see immense value in the idea of exposing young minds to female and non-binary role models – this is very much needed in today’s world where there is a big gender gap in the STEM and tech worlds. Having a role model to look up to at a young age can have a lasting positive impact in carving the life and career trajectory of the next generation of human beings.
What are you most proud of in your career, so far?
Being part of an effort –the autonomy blocks development – to bring the vision of autonomous aerial mobility to life. Project Airsim (that we announced last week at the Farnborough Airshow in the UK!), is an end-to-end software platform for developing aerial autonomy solutions.
Project AirSim provides high-fidelity simulation with a photo-realistic rendering powered by 3D real-world and synthetic/hybrid data; also offers pre-trained autonomy building-blocks and enables customers to accelerate AI training for powering drones and UAVs across use cases ranging from: Electric Vertical Take Off and Landing, Urban Air Mobility, to drones that deliver food and convenience items to large-scale infrastructure inspections.
What does an average work day look like for you?
I work for the Business Incubation Group (BIG) at Microsoft. Since we focus on “incubating” businesses, it is a true intrapreneurship environment. As part of Project AirSim with BIG, my primary focus is on building Autonomy Blocks using different machine learning algorithms to help enhance the “intelligence” of these flying machines. That means infusing the vehicle with capabilities to perceive (or “see” the world), understand, process, and act to navigate and accomplish their missions.
It is not uncommon for me to hop from working on the code to contribute to the product design process to doing aerospace industry research to enhance our product by aligning it more and more with the customers’ needs. To sum up, my average work days are filled with tasks and functions that keep me on my toes and not let the thrill of “doing something exciting and meaningful towards sustainability” tamper down!
Are there any specific skills or traits that you notice companies look for when you’re searching for roles in your field?
“T-Shaped Skills”
The concept of T-Shaped Skills has been around for a while but has recently gotten more attention in the machine learning and data science community. The T shape is a metaphor for the depth and breadth that an individual has in their skills. The vertical stem of the ‘T’ represents the depth of skills and expertise in a specific field (example from my case: deep learning algorithms for perception stack), while the horizontal bar represents a thinner but broader layer of skills, knowledge and collaboration across other disciplines and skill areas (example from my case: cloud platform, creative mindset, domain knowledge in aerospace, software engineering skills to work with large code bases).
Companies look for employees who demonstrate T-shaped ability because that makes them effective collaborators – they bring their core skillset to the table along with the ability to understand how their piece “fits” into the larger product picture.
Which qualifications have you found to be the most beneficial for securing jobs in AI?
Hands-on work experience
This has been by far has been the most beneficial qualification – when one works on a real-life data science project by rolling up the sleeves, the pace and quality of learning are tremendous compared to only taking courses. Of course, taking courses to acquaint oneself with the fundamentals and know-how is a great first step. But landing a role that allows you to be a part of a cutting-edge product development effort needs experience with, and understanding of, the real-life challenges one deals with while integrating machine learning algorithms in a product.
Has anyone ever tried to stop you from learning and developing in your professional life, or have you found the tech sector supportive?
I grew up in a small town in India where it wasn’t common to encourage girls to take up STEM careers. Growing up in the 90s, I experienced a fair amount of resistance from elders in the family as I wanted to keep studying. I come from a middle-class Indian family. My grandfather had the mentality (which, at the time was typical for society living in small towns) that investing in a girl’s education is not a good use of the constrained resources they had. I loved math and science from an early age and dreamt of pursuing a STEM career.
Fortunately, after some initial resistance, my parents (who both had master’s degrees in non-engineering majors) were supportive of my continued education beyond high school in the 2000s. They have had their concerns and complaints during my undergrad and then graduate education abroad but overall their help with securing student loans has been instrumental in my obtaining higher education.
My start in STEM wasn’t smooth. Overcoming resistance from the elders, convincing parents, working through financials, and paying the heavy student loan after graduating are different types of barriers that I faced along the way. Though it is not uncommon for the youth to find themselves in hefty student loans – the toughest part of my personal STEM journey was the internal resistance posed from within the family (elders specifically).
Instead, if I had the needed mental support from family and community, I would have been much more effective in channeling my energies toward growing my skills. Instead, I had to spend a lot of mental and emotional energy convincing myself that it is okay to go against the elder’s wisdom, invest a big sum of money in process of obtaining an education, and have the confidence that I will be able to get to the other end successfully.
Also, it is not just an “altruistic” gesture to give women a seat at the table – it is a smart business decision because many studies show that gender-diverse teams have increased productivity and overall results are boosted.
After completing my graduate education, working in the STEM sector in the US and Canada has been a great experience for me so far. I consider myself fortunate to have found managers and colleagues who were very supportive of and didn’t bring any visible biases towards females in STEM to the table. My current employer – Microsoft – is one of the big tech organisations trail-blazing the diversity and inclusion matter. The organisation is constantly nurturing a culture where D&I is in its fabric; innovations are thriving on this foundation.
That said, I am aware of the biases that women have been facing in the very same tech sector that I am a part of. They are real and need to be addressed. Awareness, authentic conversations, and non-judgemental avenues to share personal experiences (for example #metoo movements) are the first powerful steps that can help bring lasting change in this matter.
What advice would you give other women wanting to reach their career goals in technology?
Develop a “Growth Mindset”
When we were children, developing a growth mindset required that teachers and mentors reward us for the ‘efforts’ and ‘hard work’ instead of the ‘results’. Regardless of the mindset with which we were raised (growth vs. fixed), as adult women working in the tech industry, it is in our own hands to consciously develop a ‘growth mindset’ where we keep our minds open to exploring possibilities we thought were never under our reach. This means cultivating interest and learning fields that are not our core areas of expertise. As an example, if you are a hard-core programmer and have shied away from public speaking for all these years, then run no more. Embrace the discomfort and possibly a few failures by putting yourself out there for speaking opportunities.
You will be surprised to see how many opportunities open up when you take this cross-disciplinary road of blending your core expertise with additional (and sometimes tangential) interests. This way, having a “Growth Mindset” will help you overcome all internal obstacles, saying “this is not your area-of-expertise” or “you are not good enough to tackle this”, which holds you back from fulfilling your dreams.
Cast wider-net
“Data Scientist” is one of the hottest job titles out there these days. Yes, we have heard so many times that data scientists are in demand, and this job is considered future-proof in many ways.
But here is something that is less talked about – The ability to draw insights from data is needed in ALL disciplines. Data science is not just about fancy “Natural Language Processing Models” such as GPT3s – it is also about finding ways to run the HVAC more efficiently and about discovering new materials using machine learning that can make the next breakthrough the energy storage technology and so much more. So, if you are inclined to choose data science as your career, then cast a wider net! So many disciplines and industries are in need of data scientists.
Entering the world of work can be daunting. Do you have any words of advice for anyone feeling overwhelmed?
Perspective
On the time axis, learn to zoom-in and zoom-out seamlessly. That is, in short-term things may be seeming chaotic and your career plan not working out as you have imagined and/or wanted it. But the key is to remember/keep accounting for incremental efforts that you are putting in on a regular basis. When baby steps are taken with consistency, the results are bound to come – tomorrow or the day after.
Importance of mental health
Never discount the importance of mental health. It is a very personal thing you need to take care of. Treat it as an independent life goal. It should not be a function of how fast or slow your professional career is growing or how your personal/professional relationships are or aren’t flourishing.
Have the mindset that one’s mental health, at its core, is one’s own responsibility. If you are feeling overwhelmed due to any fluctuations in life (professional or personal) – seek help. Meditate. Take long meditative walks in nature. Read inspiring literature. Slow down. Hold on to a zoomed-out perspective in the face of short-term failures. Have your own definition of success and don’t just go by the world’s “perception” of success. When a project fails – remind yourself that “this failure is an event that I was a part of. The project’s failure does NOT mean I am a failure”.