Model Engineer

CLERA, LLC
San Francisco, CA, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$200,000.0 - $300,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Distributed Systems Networking Hardware Python (Programming Language) Machine Learning Network Architecture Tensorflow Management of Software Versions Wireless Access Point Computer Networking Systems Pytorch Delivery Pipeline
+1 more
Machine Learning Operations

Job description

This is a rare opportunity to join the founding core engineering team of a fast-growing company building frontier AI for enterprise internet infrastructure. The company designs and manufactures its own networking hardware - controllers, switches, and wireless access points - and manages full-stack installation and operations for business customers. This full-stack ownership gives the team unique visibility and a proprietary dataset unlike anything available in academia or at most tech companies.

As a Model Engineer, you’ll help define the intelligence layer for this infrastructure: training models that deeply understand networked systems, anticipate failure before it happens, and take autonomous corrective action. You’ll work at the intersection of applied ML research and production systems engineering, collaborating closely across hardware and software teams.

What You’ll Do

  • Train end-to-end models applied to fault prediction, network state modeling, and autonomous repair.
  • Build multi-modal models over structured networking data and implement function-calling to make network-wide decisions autonomously.
  • Evaluate model performance in both real-world hardware and virtualized environments, iterating to improve reliability and efficiency.
  • Contribute to shaping the technical direction and culture of a new applied research organization from the ground up.

Requirements

Required:

  • Hands-on experience building and training ML models for large-scale infrastructure, monitoring, automation, or systems optimization - this is a dealbreaker requirement.
  • Experience working with distributed systems data, telemetry, and anomaly detection to improve reliability and performance.
  • Proficiency in Python and one or more ML frameworks (e.g., PyTorch, TensorFlow).
  • Experience with MLOps: model deployment, monitoring, versioning, and automation pipelines in production.
  • Strong cross-functional communication skills, including presenting findings to both technical and non-technical stakeholders.
  • Strong CS fundamentals.
  • Willingness to work on-site in San Francisco, CA (Mission District).

Nice to Have:

  • Prior experience at a startup or fast-paced early-stage company; comfort operating with ambiguity and influencing without formal authority.
  • Background in networking, systems, or physical infrastructure domains.

Benefits & conditions

$200,000 - $300,000 a year - Full-time

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