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Saurav Dhakad is a Machine Learning Engineer currently based in Seattle, Washington. Holding a Master’s degree in Computer Science from Columbia University, Saurav has over three years of experience in the field, focusing on Computer Vision and 3D Machine Learning.
Saurav’s career spans significant roles at diverse organizations, including a current position as a Machine Learning Engineer with the Avatars R&D team at Genies, a cutting-edge startup specializing in avatar technology. Previously, he dedicated over three years to the Applied Machine Learning Research (AMLR) team at Unity, where he focused on leveraging synthetic data to enhance computer vision model performance.
With a solid academic foundation, Saurav has contributed to the research community through published papers and valuable roles such as Research Assistant at Columbia University. Renowned for his transformative approach and unwavering commitment to innovation, Saurav excels in solving real-world problems, showcasing technical expertise in MLOps, ML Research, Design, and CI/CD systems. Thriving in collaborative and fast-paced environments, he continues to leave a lasting impact on the ever-evolving landscape of artificial intelligence.
Connect with Saurav to learn more.
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Here are Five Things We Cover:
- Early career focus: Saurav emphasizes the value of seeking opportunities where one can gain exposure to the overall project pipeline and potentially lead a project, rather than being confined to a narrow role or smaller part of a project.
- Importance of mentorship: Saurav highlights the significance of having a mentor in the field of machine learning to provide guidance and support when encountering challenges, rather than seeking quick fixes.
- Diverse skill development: Saurav recommends starting with the fundamentals of machine learning and then exploring various areas within the field to determine a specific focus, gradually delving deeper into a chosen specialization.
- Research and collaboration: Saurav illustrates the process of problem-solving in complex projects, involving discussions with colleagues and researching existing studies to develop innovative solutions.
- Networking on LinkedIn: Saurav suggests using LinkedIn as an effective platform for networking and connecting with professionals in the industry to expand one’s knowledge and opportunities.
These insights provide valuable guidance for individuals aiming to build a career in the dynamic and challenging field of machine learning and 3D technology.
Here are Three Actionable Takeaways From This Episode
- Find a mentor: Seek guidance and advice from someone experienced in the field. A mentor can provide valuable insights and help you navigate challenges in your career. Look for someone who can offer advice on next steps and provide direction when you feel stuck.
- Explore the breadth of machine learning: Start by learning the fundamentals of machine learning and then delve into different areas within the field. Gain exposure to various aspects of machine learning to determine which area interests you the most. Once you have a broad understanding, focus on diving deeper into a specific area that aligns with your interests and goals.
- Utilize online resources: Take advantage of the numerous online resources available, such as YouTube tutorials and Google search, to enhance your understanding of machine learning concepts. Use these resources to address any challenges you encounter and further strengthen your knowledge in the field.