Marct AI 6/1 - Creator Economy, Precise Gene Vectors, Greylock Sec+AI Research Meetup, P-ai Demo Day, Data Analyst Interview Guide, and more!

Welcome to Marct AI edition #5, an exclusive/curated email thread for a first-look at some exciting AI-related startup opportunities + bonus gigs.

I'll put some brief thoughts with each opportunity in italics (look for AK's thoughts) on why I decided to include it/what makes it interesting compared to the thousands of other postings on the interweb. Opportunities are full-time unless indicated otherwise. Still experimenting with the format, style, and organization so expect to see some changes.

Full-time and Internships:

Beacons AI - Fullstack Engineer, Product Designer: "link in bio" website builder for creators.

AK's thoughts: exponential growth (+5k signups/day, 300k+ users including Sia & The Chainsmokers); strong technical team with ML PhD from Stanford backed by a16z, Naval, Li Jin, etc; new wave of tooling for the creator-economy (emerging/expanding market); help creators personalize content, take donations, connect with audience through ML. [mention you saw this opportunity from Marct AI]

Ironclad - Data Engineer: contract lifecycle management.

AK's thoughts: excellent product created by lawyers to make painful legal parts of the business streamlined; digital workflows (dynamically capturing critical info), collaboration (redline, editions, ad-hoc conversations), data platforms (centralized and sychronoized repo); c.f. Figma for wireframing and design, Pitch for presentations; contracts are the atomic unit of business yet very complex; mitigate risk and increase deal speed in a meaningful way.

Curai - (Consumer Product Manager, Machine Learning Engineer, Machine Learning Research) Interns: high-quality and minimal barrier primary care.

AK's thoughts: Personally interviewed with the very mission-driven team (ended up pursuing other opportunities); get matched to a project that fits your interest/experience and high-conversion rate to ft roles; high-calibre leadership from Google, Netflix, Stanford; create scalable systems compatible with all kinds of medical and healthcare data; checkout some of their projects in Curai's active blog and some of their published research.

Dyno Therapeutics - Data Scientist/Computational Biologist: gene therapy through AI-powered vectors.

AK's thoughts: interdisciplinary molecular+synthetic biology at the micro-level with marco-scale impact; build targeted, multi-functional, disease-specific AAV capsids to safely and precisely deliver payloads; deep-tech, moon-shot project tackled by cutting-edge experts with deep domain expertise; backed by incredible investors and scientists; if successful, could augment and unlock countless usecases; biology is eating the world and it's time to heal.

Coveo - (Backend, NLP applied, NLP research, Designer, BI Developer, Software Developer, Fullstack Developer) Interns: tailored and personalized digital experience.

AK's thoughts: deeply R&D focused company (as you can tell by the hires across eng); one of the best AI companies in Canada with a well-executed and thoughtful internship program (just spoke to lead student recruiter about this); multi-dimensioned problem involving search & discovery, cloud, real-time recommendations, behavior-based personalizations, intelligent knowledge management and chat, etc; check out this internship blog.

If you like what you are reading, please forward this to a friend who might enjoy this content. If you are just seeing this email for the first time, join this exclusive thread by filling out the form here :)

Misc, Random, Interesting Opportunities:

Greylock's Student in Security Tech Meetup:

Join Greylock's quarterly Students in Security Tech meetup on June 16th at 5pm PT/8pm ET to hear from Christopher Choquette (AI Resident at Google) and Soo-Jin Moon (CMU and Google Network Infastructure), in a conversation moderated by Laura Zhukas. After the discussion, you'll have a chance to network with peers across North America in small groups. RSVP required [click link above for details]. Full disclosure: I'm helping lead this group:)

Watch P-ai's spring Demo Day, 7 project presentations and yearly recap:

P-ai.org is the modern incubator for AI/ML projects and ideas at the Claremont Colleges. Need inspiration for personal projects? Want to learn how to plan an end-to-end ML project? Curious to see what a sharp group of students are working on and what is interesting to them? Watch the Demo Day recording! p.s. you can watch at 2x speed too!

The Data Analyst Interview Guide, by Diana Cherny:

Useful resource for Data Analytics, Business Intelligence Analyst positions (SQL, Statistics, Choosing and Evaluating Metrics, Dashboard, etc).

If you've read this far, tell me a problem that bothers you the most when you are doing ML projects! For me, it's the insufficient documentation for fine-tuning ML models like random-forests in sklearn.

anyways, thanks for reading! let me know what you liked/didn’t, what you want to see, and if you do end up applying to something here, by emailing me at [email protected] :)

Cheers,

A.K.