Job description
Our Mission
At Phygtl, we are solving the problem of student social isolation — a challenge affecting 60%+ of today’s students, contributing to rising depression and anxiety.
We build technology that can reduce isolation by up to 40%, by helping students form real campus connections through shared real-world moments — bridging the physical and digital worlds.
Who We Are
Headquartered in San Francisco, our team includes PhDs from Stanford, UC Berkeley, MIT, and Carnegie Mellon, alongside builders from Niantic, Meta, Magic Leap, Riot Games, Ubisoft, and Zynga. Led by a Silicon Valley-based serial entrepreneur, we’re united by a mission to rescue next-gen from Social Atrophy.
Our Moat
Phygtl builds systems that help students meet and build identity in real life. Vyry is a context-aware initiation engine where quests end in physical action. Retention is earned through participation — not notifications.
The Role
You’ll join the team building Vyry, a mobile app that helps students meet in real life through short, coordinated campus quests.
Right now, our focus is Quest Participation optimization: keeping peers on the quest screen while they coordinate via chat, voice, and AR Meet, without state glitches, drop-offs, or broken realtime behavior.
This role is not about “building chatbots.”
It’s about shipping realtime intelligence inside a live social product, where state correctness, latency, and user trust matter.
What You’ll Work On
Designing context-aware quest logic (physical + social + temporal signals)
Detecting stall or drop-off conditions during coordination
Suggesting structured micro-actions that increase completion probability
Instrumenting evaluation loops tied to measurable behavioral outcomes
Shipping production-facing components
You will operate on top of existing real-time systems — not rebuild infrastructure.
What We’re Looking For
You are:
A strong computer science or engineering student
Someone who has shipped real systems (GitHub required)
Comfortable reasoning about state transitions and edge cases
Curious about AI systems beyond simple prompt usage
Able to move from idea → working prototype quickly
You should be able to:
Design a simple state-aware workflow
Think through failure modes
Explain tradeoffs (latency, cost, reliability)
Tie technical decisions to measurable outcomes
Bonus if you’ve built:
Agentic workflows
Multiplayer or event-driven systems
Evaluation pipelines for AI systems
Side projects used by real users
How We Evaluate
We prioritize:
Systems clarity (state + failure thinking)
Execution speed
Ownership
Depth over pedigree
Why Join Phygtl
Work on a Real Behavioral Problem. You won’t optimize clicks. You’ll design systems that influence real-world human coordination and identity formation.
This is AI applied to physical behavior — not interface optimization.
Ship Systems That Matter
Your work will tie directly to:
IRL Quest Completion Rate
D30 Retention
You won’t build experiments that disappear. You’ll ship components used by live campus communities.
Learn From Operators Who’ve Built at Scale
You’ll work with the foundering team, engineers and researchers from:
Founder DNA
Roblox (LLM + search systems)
Niantic (AR + real-world coordination)
Stanford / Berkeley / MIT / CMU
Expect depth, not hand-holding.
Operate in a High-Bar, Low-Bureaucracy Environment
We value:
Meritocracy over pedigree
Shipped systems over slide decks
Clear thinking over buzzwords
Ownership comes early. Responsibility scales with performance.
Build a Rare Skill Set
You’ll gain experience at the intersection of:
Agentic AI systems
Real-time coordination
Behavioral metrics
Spatial computing
Few internships operate at this boundary.
Compensation & Structure
Competitive compensation
Flexible remote structure
FT 3 months or PT 6 months
High ownership, small team
Apply
CV
GitHub
A concise architecture walkthrough of one system you built
One failure you debugged (what broke, why, what changed)
A short note (≤300 words) on how you’d increase IRL Quest Completion by 15%
We review for depth, not buzzwords.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.