Listen here:
Currently serving as a dynamic Machine Learning Engineer at Instacart, Sai bring my expertise to cutting-edge projects at the forefront of technological progress. With a successful track record as a Software Engineer at industry giants such as Google, Sai specialized in personalized recommendations within the YouTube Suggest team. At Microsoft’s HoloLens division, Sai delved into machine learning and deep learning, leveraging Eye Tracking for innovative solutions. Sai’s stint at Cisco involved championing SDN solutions for Data center products, while at Schlumberger, he explored “Exploiting Computer Vision at the Edge using Deep Learning.” Pioneering a centralized system for real-time power consumption at AP Transco and optimizing algorithms for Super Computers at the National Atmospheric Research Laboratories underline hia diverse skill set.
Passionate about Computer Vision, Deep Learning, IoT, Data Science, Software Engineering, and Software Development, Sai’s journey is marked by an unyielding thirst for innovation. Beyond technical acumen, Sai’s exceptional collaboration skills distinguish himself. As a proven self-starter, Sai excels in challenging environments, consistently delivering excellence. Fueled by an unwavering commitment to innovation, Sai’s professional voyage reflects a relentless pursuit of impactful contributions across various domains.
Connect with Sai Teja Chava to learn more.
Listen to the Podcast Here, or Find it Wherever You Get Your Podcasts:
Here are Five Things We Cover:
- Interview Preparation Is Key: Sai highlights the necessity of a dedicated preparation phase before interviewing for tech roles. Candidates should focus significantly on coding practice and comprehension of machine learning concepts, but should not neglect behavioral and leadership questions, which vary in importance from company to company.
- Practical Experience Trumps Certifications: While certifications in specialized areas like deep learning and machine learning can provide foundational knowledge, Sai underscores the critical role that project-based work and practical experience play in getting noticed by top tech companies.
- Importance of a Strong Personal Profile: For those looking to land a job in tech, maintaining an active LinkedIn presence and nurturing a Github profile are crucial. Displaying personal projects, internship experiences, and relevant coursework can considerably enhance a job seeker’s visibility to recruiters.
- The Traits of High Performers: Sai touches on certain traits displayed by high-performing machine learning engineers. These include a balance of humility and confidence, commitment to continuous learning through reading research papers and attending conferences, and strong mathematical fundamentals.
- Proactive Learning Is Essential: Sai’s story echoes the sentiment that opportunities favor the prepared mind. He encourages college students and aspiring engineers to continuously learn, take on side projects, and stay equipped for opportunities, underlining that the journey into machine learning begins long before the actual job search.
Here are Three Actionable Takeaways From This Episode
- Develop Technical Proficiency: Work on personal tech projects or contribute to open-source to showcase your skills. Take online courses in machine learning and coding, especially those with hands-on projects.
- Enhance Professional Presence: Keep your LinkedIn updated with projects, experiences, and skills. Network within the tech community and seek mentorship or advice from professionals.
- Tailor Your Interview Prep: Allocate focused time for interview preparation, practicing both coding and machine learning concepts. Research the specific interview styles of target companies and practice accordingly, including behavioral question frameworks like the STAR method.