Senior Machine Learning Ops Engineer, Hayden AI

$200-260k

+ Equity + Bonus

AWS

GCP

Python

Linux

Senior and Expert level

San Francisco Bay Area

3 days a week in office

AI-powered smart traffic enforcement

Open for applications

AI-powered smart traffic enforcement

101-200 employees

B2BTravelArtificial IntelligenceTransportManufacturingBig dataDeep TechComputer VisionMachine LearningSaaSMobile

Open for applications

$200-260k

+ Equity + Bonus

AWS

GCP

Python

Linux

Senior and Expert level

San Francisco Bay Area

3 days a week in office

101-200 employees

B2BTravelArtificial IntelligenceTransportManufacturingBig dataDeep TechComputer VisionMachine LearningSaaSMobile

Company mission

To harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.

Job

Company

Role

Who you are

A Bachelors Degree or a Masters Degree in Computer Science, Electrical Engineering, or a related field
Core Skills: General Software Engineering skills with 6+ years of programming experience in python and the surrounding tooling ecosystem along with familiarity in linux and expertise in infrastructure, cloud and/or MLOps,
Personal Attributes: Team player, good communication skills, self starter
Strong teamwork and communication skills to collaborate with cross-functional teams, including ML and software engineers
Nice to Have: Experience building MLOps pipelines for deep learning based perception solutions on AWS or GCP

What the job involves

As a Senior MLOps Engineer within the Perception Deep Learning team, you will lead the design and evolution of our machine learning platform, enabling teams to build, deploy, and scale intelligent systems with reliability and speed
In this role, you will partner closely with perception, deep learning and platform engineers to build infrastructure to train and operationalize machine learning models and drive best practices across the ML lifecycle
You will play a key role in shaping the architecture of our ML infrastructure, from data ingestion and training pipelines to deployment, monitoring, and governance
As a senior member of the team, you will influence technical strategy, mentor engineers, and champion a culture of reproducibility, observability, and continuous improvement
Architect, design, deploy, and operate scalable cloud-based MLOps platforms and workflows that enable efficient training, evaluation, deployment, monitoring, and lifecycle management of AI/ML models
Own the technical strategy and evolution of ML infrastructure, identifying architectural bottlenecks and driving cross-functional initiatives to improve developer productivity, experimentation velocity, scalability, and operational efficiency
Build robust, reliable, and automated systems that enable teams to ship new models and features rapidly while maintaining high standards for quality, reproducibility, observability, security, and production reliability
Define and implement infrastructure optimization strategies that balance performance, scalability, reliability, and cost across cloud and compute resources
Evaluate emerging tools, technologies, and industry best practices in MLOps, cloud infrastructure, and ML systems, and lead their adoption where they can meaningfully improve ML development and production workflows
Establish engineering best practices for ML infrastructure, including system design, code quality, testing, CI/CD, monitoring, documentation, and operational readiness
Provide technical leadership and mentorship to engineers, lead design and code reviews, and help raise the engineering quality and technical capabilities of the broader team
Partner closely with ML engineers, researchers, data engineers, and product teams to translate evolving AI/ML requirements into scalable and maintainable infrastructure solutions
Drive complex, ambiguous infrastructure projects from technical strategy and architecture through implementation, production deployment, and long-term operational ownership

Our take

Cities around the world are dealing with clogged bus lanes, blocked stops, and traffic violations that slow down public transit and put people at risk. It's a huge problem, but one that remains difficult to monitor or mitigate effectively.

Hayden AI is tackling this problem with its smart, bus-mounted cameras powered by AI. They automatically detect when vehicles block bus lanes or stops, helping cities gather real-time data and take action to improve safety and traffic flow.

Already in use in cities like New York, LA, Barcelona and Braga, it's a transformative idea that can keep buses moving and riders safe. The company has raised considerable funding and is growing fast, and in 2026 received approval to begin serving local authorities across the UK.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 4 rounds)

Aug 2022

$4m

LATE VC

Sep 2020

$35m

SERIES B

Total funding: $52.6m

Company HQ

China Basin, San Francisco, CA

Leadership

Vaibhav Ghadiok

(CTO & Co-Founder)

Previously a Robotics Engineer at Nixie Labs, Head of Mapping at NAUTO, and Navigation & Perception Lead at Visible Sensors.

Marty Beard

(CEO)

Previously Co-Founder and CEO of alwaysAI, a vision AI company, as well as C-level executive at leading public and private companies, including Sybase, LiveOps and BlackBerry.

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