MLOps Engineer

Posted 18 Days Ago
Be an Early Applicant
San Francisco, CA
In-Office
140K-175K Annually
Senior level
Information Technology • Internet of Things
AI Landscaping Takeoffs & Estimates
The Role
Design, build, and maintain production ML deployment, serving, and inference pipelines. Implement infrastructure-as-code (Terraform), CI/CD, GPU provisioning and cost optimization. Build monitoring/observability, collaborate with ML and full-stack teams, and occasionally contribute to React/Django product work.
Summary Generated by Built In
Position Overview

Bobyard builds AI systems that automate takeoffs for contractors, saving them dozens of hours per project. Delivering this reliably at scale requires production-grade ML infrastructure, deployment systems, and cloud architecture that do not break under real customer usage.

You will have very high autonomy in designing, executing, and iterating on our infrastructure. We are a startup, and we move fast. You will be the person responsible for turning research models into reliable production systems and building the foundation that allows engineering to ship quickly and safely. We look for world-class engineers who think in systems, take ownership of reliability and cost, and can go heads down to build durable infrastructure.

Responsibilities
  • Design and maintain ML deployment and model serving infrastructure

  • Build end-to-end pipelines for model packaging, inference, monitoring, and scaling

  • Implement infrastructure-as-code across all cloud resources (Terraform target state)

  • Own CI/CD pipelines, release processes, and deployment automation

  • Manage GPU provisioning, utilization, and cloud cost optimization

  • Build monitoring, alerting, and observability across services

  • Work closely with ML and fullstack engineering to ship production systems

  • Contribute to product development (React + Django) when infrastructure priorities allow

Desired Attributes
  • Strong PyTorch knowledge with understanding of speed and memory bottlenecks and inference optimization

  • Comfortable managing GPU services (AWS, GCP,...), model containers, versioning and scaling

  • Experience owning infrastructure at a small team or startup

  • Cloud-native and pragmatic — chooses simple, reliable solutions

  • High ownership mindset — you don’t wait to be told what to fix

  • Cost-aware and disciplined about cloud spend

  • Full-stack capable — can ship features in React or Django when needed

  • Fast learner who can navigate unfamiliar systems and tools quickly

  • Passion for building foundational systems that enable product velocity

This is a full-time & in-person role in the SF Bay Area. Learning rate and ownership are vital factors. If you can build the infrastructure that our models and customers depend on — at the speed and quality the market demands (or if you can prove that you will acquire the ability to do so fast enough), we would love to work with you.

Top Skills

AWS
Ci/Cd
Containers
Django
GCP
Gpu Provisioning
Model Serving
Monitoring
Observability
PyTorch
React
Terraform
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The Company
HQ: San Francisco, California
30 Employees

What We Do

Construction is one of the largest industries in the world, but it is also one of the least technologically innovative spaces. Conducting fast and accurate cost estimates is a massive pain point. Bobyard automates the construction takeoff process with CV and NLP models to make cost estimates 10x faster while eliminating mistakes.

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