596,392open jobs
27,417companies
85,006added this week
Browse all
Salary
$160k – $180k per year
Location
In office (San Francisco)
Seniority
Middle · 4+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match

About Bobyard

Construction is a multi-trillion industry running on PDFs, rulers, and 1990s software. The biggest choke point is the cost estimate. Takeoffs are manual, slow, and one mistake blows millions. We use computer vision and NLP to read drawings like an expert estimator, 10x faster and with fewer mistakes. We're backed by 8VC, Primary, and Pear.

About the role

You'll own a model-powered product surface end to end: not writing specs and handing them off, but being the person engineering and customers both come to when the question is "why did the model do that, and what do we do about it."

What you'll do

  • Own the roadmap for a model-powered product surface, from customer problem to shipped feature

  • Read eval reports and confusion matrices well enough to argue with the CV engineers, not just relay their conclusions

  • Make and defend accuracy/speed/cost tradeoffs - in the room with engineering, and directly with customers

  • Build and maintain eval sets that keep the team honest about model performance

  • Decide when a model is actually ready to ship - not based on aggregate accuracy, but on which failure modes are cheap to catch downstream and which are expensive to miss

  • Turn ambiguous customer complaints ("it missed something") into a specific, testable model or UX fix

  • Work daily with our CV and ML engineers as a peer who understands the model, not a translator layer

What we're looking for

  • 4+ years in product, with real ownership of a model-powered feature (not just "worked with" a data science team)

  • Fluent in model evaluation - precision, recall, false positive/negative tradeoffs - and can reason about when "85% accurate" is good enough versus when it isn't, based on the cost of the specific errors, not just the aggregate number

  • Has shipped 0-to-1 or a major iteration on an ML/CV-driven product in B2B SaaS

  • Comfortable being the last line of defense on "will this model actually work" for customers and execs

  • Fast learner - no construction background required, but you'll need to be dangerous in it within 30 days

  • Ships fast, iterates in public, doesn't hide behind process

Nice to have

  • Prior experience specifically in computer vision (vs. NLP/LLM-only)

  • Background at a company like Scale AI, Labelbox, Samsara, Matterport, Cape Analytics, or DroneDeploy

  • Comfortable in Figma and reading code, even if you don't ship it

What we offer

  • $160K-$180K base + equity

  • Full-time, in-person in San Francisco - we build together

Comp Philosophy

We are proud to offer competitive, top-of-market compensation because we want to celebrate the dedicated people who ship amazing work and drive our success. Our individual compensation is thoughtfully tailored based on your role, experience, and contributions, alongside performance-based rewards.

Free account
Stop reading job ads. Get the ones that fit.
One free account turns this page into a shortlist built around your stack, your level and your pay.
Match on every job. Stack, seniority, pay and location, scored against your profile.
596,392 open roles. Read straight off company career pages, refreshed every day.
Unlimited applications. Every one you send is tracked in one place, on-site or on a company board.
3 tailored CVs a month. Rewritten for the exact job you are applying to. Included free.
Create a free account Continue with Google
Free forever. No card. Under a minute.

Your match

How well do you fit this role?
Two answers are enough for a real match. No account needed.
Check my fit
Answers stay in this browser until you create an account.

Recommended for you based on this role

Similar stack
Same company
San Francisco
Lead ML & AI Engineer 6 hours ago
In office • 3+ years exp • Bachelor's Degree
SQL
AI/ML
LangChain
Computer Vision
AI Agents
NLP
CrewAI
RAG
Amazon SageMaker
Feature Store
DevOps
CI/CD
Jenkins
AWS
Docker
Kubernetes
AWS Lambda
Amazon S3
Management
Agile
Apply
Remote/Hybrid • 10+ years exp
AI/ML
Quantization
Computer Vision
ONNX
TensorRT
PyTorch
Synthetic Data
Edge AI
Robotics
nuScenes SDK
Sim-to-Real
Apply
$195k – $210k per year • In office • Bachelor's Degree
Python
AI/ML
Fine-tuning
Multimodal AI
Diffusion Models
Computer Vision
PyTorch
World Models
Apply
Lead Data Scientist 6 hours ago
$160k – $170k per year • In office
Python
SQL
AI/ML
Multimodal AI
Computer Vision
Synthetic Data
Apply
In office • 10+ years exp • Master's Degree
Python
SQL
MATLAB
SAS
AI/ML
Hadoop
Spark
Computer Vision
Apply
Senior Data Analyst 9 hours ago
$140k – $160k per year • In office • Full-Time • 5+ years exp • Bachelor's Degree • San Francisco
Python
SQL
Databases
Google BigQuery
BigQuery
AI/ML
dbt
DevOps
GCP
Cybersecurity
SOC 2
Analytics
ETL/ELT
Apply
Program Manager 17 days ago
$120k – $150k per year • In office • Full-Time • San Francisco
Management
Linear
Jira
Apply
$100k – $125k per year • In office • Full-Time • San Francisco
DevOps
SLI/SLO/SLA
Apply
$160k – $185k per year • In office • Full-Time • 6+ years exp • San Francisco
SQL
Management
Intercom
Marketing
Salesforce
HubSpot
Apply
$115k – $135k per year • In office • Full-Time • San Francisco
Marketing
HubSpot
Apply
$115k – $180k per year • Remote/Hybrid • Full-Time • 4+ years exp • San Francisco • Seattle • Raleigh • New York
Apply
$97k – $124k per year • In office • Full-Time • 1+ year exp • San Francisco
Design
Canva
Management
Slack
Google Workspace
Apply
$200k – $240k per year • Remote/Hybrid • San Francisco
AI/ML
AI Agents
LLM
RAG
Apply
$152k – $301k per year (Estimated) • In office • Full-Time • Bachelor's Degree • Dallas • Austin • San Francisco • Fort Worth • Los Angeles
Marketing
Salesforce
Apply
$285k – $335k per year • Equity • In office • Full-Time • 10+ years exp • San Francisco
DevOps
VMWare
containerd
Kubernetes
KVM
QEMU
Hyper-V
Apply
See all jobs
This is one of many
596,392 more open roles from verified company boards, updated every day.