Research Analyst
Kindred Ventures
About Kindred Ventures
Kindred Ventures is an early-stage venture capital firm, backing visionary and relentless founders building the future using technology and science. Founded in 2014, Kindred focuses on seed-stage investments – backing startups early before product-market fit and often pre-product. We are multi-theme specialists investing in startups across AI, consumer tech, crypto/web3, fintech, health & wellness, mobility & logistics and tools & infrastructure. Kindred Ventures is led by Steve Jang and Kanyi Maqubela and has over $500M in assets under management across multiple funds.
The Role
We are seeking a highly skilled and motivated Research Analyst to join our team focused on frontier technologies and artificial intelligence. As a key member of our research program, you will play a crucial role in developing our thesis across various technology themes and engage in the investment process, providing primary and secondary market intelligence and assessments of new technologies.
Responsibilities:
- Monitor and analyze new model developments and emerging trends in Artificial Intelligence and other frontier technologies.
- Conduct in-depth evaluations of the technical feasibility and potential impact of AI/ML solutions proposed by startups.
- Collaborate with the investment team to evaluate investment theme areas, analyze emerging products and technologies, and contribute technical research to memos and presentations.
- Publish internal and external technical research based on Kindred’s focus areas..
- Stay informed on the latest AI/ML developments by attending industry conferences and events.
- Work with the investment and community teams on conferences, portfolio events, founder summits, and other events.
- Support portfolio companies with technical feedback and guidance.
Qualifications:
- Deep technical understanding of AI/ML, particularly in areas like deep learning, natural language processing, computer vision, and reinforcement learning.
- Familiarity with popular AI/ML frameworks and tools, such as TensorFlow and PyTorch.
- Experience with or understanding of applying AI/ML in various products and in real-world business contexts.
- Advanced degree (MS or PhD) in Computer Science, Machine Learning, Artificial Intelligence, or equivalent experience.
- Minimum of 1-3 years of experience in AI/ML research or applied AI development, preferably at a late-stage or public tech company, a leading AI research lab, or a top-tier academic program.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences.
- Experience with or a strong interest in the venture capital and startup ecosystems.
- Ability to work independently and collaboratively in a fast-paced, dynamic setting.
- Experience publishing and leading research projects from conception to completion.
Preferred:
- Experience in evaluating and managing both research and engineering teams and projects at a foundational model company or a major cloud platform.
- Proven publication record in top AI/ML conferences or journals.
- Frequent contributor to posters at ICML and NeurIPS.
What We Offer:
- Build a body of work in research exploring state-of-the-art advancements in AI and engage with world-class talent from around the globe.
- Opportunity to participate in and learn from the investment process, including initial pitches, investment committee discussions, and portfolio support.
- Ability to help shape the future by supporting our investments in key technologies and innovative startups.
- A collaborative work environment with a team of experienced investors and operators.
- A competitive compensation package.
If you’re passionate about AI/ML and eager to play a pivotal role in identifying and supporting the next generation of groundbreaking companies, we’d love to hear from you.
BenefitsÂ
This role is eligible to participate in the Kindred Ventures benefit plans, including platinum health, dental, vision, disability, life insurance, 401K plan, and paid discretionary vacation time.