Senior MLOps Engineer, Teleo

$200-250k

Docker

Kubernetes

Linux

Airflow

CUDA

PyTorch

Drift

Junior and Mid level

San Francisco Bay Area

Office located in Palo Alto, CA

Autonomous construction robotics

Be an early applicant

Autonomous construction robotics

21-100 employees

B2BEnterpriseRoboticsConstructionComputer VisionAutomation

Be an early applicant

$200-250k

Docker

Kubernetes

Linux

Airflow

CUDA

PyTorch

Drift

Junior and Mid level

San Francisco Bay Area

Office located in Palo Alto, CA

21-100 employees

B2BEnterpriseRoboticsConstructionComputer VisionAutomation

Company mission

Teleo's mission is to revolutionize how we build the world.

Job

Company

Role

Who you are

2+ years in MLOps / Infra / ML Platform
Deep experience with PyTorch, CUDA-aware workflows
Strong Linux + systems fundamentals
Proven experience deploying models at scale (not just notebooks)

Desirable

Training orchestration: Ray, Slurm, Kubernetes, Airflow
Model lifecycle: Weights & Biases, MLflow, custom registries
Containers: Docker, multi-arch builds
Inference optimization: TensorRT, ONNX, Triton
Monitoring: metrics, logs, alerts for ML systems
Experience with autonomy or robotics
Edge deployment constraints (latency, power, thermal)
Data versioning tools (DVC, LakeFS)

What the job involves

Own the reliability, scalability, and velocity of model training and deployment for autonomy systems. Turn experimental models into dependable production services
Design and operate end-to-end ML infrastructure: training, evaluation, deployment, monitoring
Build CI/CD for ML (model versioning, promotion, rollback, canarying)
Own model observability: drift detection, performance regression, data health
Optimize GPU utilization across training and inference (on-prem + cloud)
Support edge deployment (Jetson / Orin / x86 + GPU)
Work closely with perception and autonomy teams to reduce friction from research to production

Our take

Operating a massive piece of heavy equipment like a bullddozer for 8-10 hours a day is a challenging job. It's tiring, unsafe and requires a great deal of synchronisation with other workers and vehicles on the job. Teleo is lightening this burden for construction teams with remote and autonomous control of heavy equipment.

The startup has pursued a pragmatic “crawl-walk-run” approach to deliver the benefits of supervised autonomy now. Instead of having each machine in a fleet operated by a driver in a cab, they’re all being controlled remotely by a single human operator miles away from the job site.

The hope is that the technology matures toward fully autonomous heavy equipment operation. Like any new, next-generation technology, it can take some getting used to. However construction workers are simply adapting to robots on site as a another tool to get the job done, putting Teleo in a strong position as it sets out to disrupt the construction industry.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 4 rounds)

Nov 2024

$16.2m

SERIES A

Jun 2022

$12m

SERIES A

Total funding: $36.3m

Company HQ

Ventura, Palo Alto, CA

Leadership

Rom Clement

(CTO & Co-Founder)

Previously Head of hardware & Technology Strategist at Lyft, working in self-driving. Before that, worked as a Senior Engineering Manager at Google in Google Maps. At Google Fiber, they grew a team responsible for the development of laser telecommunication systems for space and aerial applications. Rom has a master’s degree in aerospace engineering from the University of Michigan.

Vinay Shet

(CEO & Co-Founder)

Prior to Teleo, they were the Director of Product Management at Lyft working on building Lyft's self-driving cars. Prior to Lyft, Vinay led Product Management at Google Street View, Google Maps, and Google reCAPTCHA launching several consumer products used by millions of users worldwide. Vinay has a Ph.D. in Computer Science, focusing on Computer Vision from the University of Maryland.

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