Senior Engineer, Machine Learning, Vision

Sorry, this job was removed at 08:53 p.m. (UTC) on Wednesday, Sep 23, 2026
3 Locations
In-Office or Remote
115K-172K Annually
Senior level
Hardware • Software
The Role
Build and ship machine learning and computer vision capabilities for industrial visual inspection products. Responsibilities include developing model training, labeling, dataset management, evaluation, and regression pipelines; optimizing inference for edge hardware; debugging models with customer data; and supporting production deployments. The role also contributes to ML engineering practices, reviews, and AI-assisted development workflows.
Summary Generated by Built In

Rockwell Automation is a global technology leader focused on helping the world’s manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better.

We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that’s you we would love to have you join us!

Job Description

Position Summary:

Rockwell Automation is building FT Analytics Vision machine vision and visual inspection into the Automation Control Software portfolio, alongside Studio 5000 Logix Designer, FactoryTalk Optix, and Data Mosaix. You will implement the machine learning capabilities customers actually touch - the self-learning inspection tools, color and measurement tools, and the training workflows that let a plant engineer teach the system a new defect without a data scientist in the room.
This is an implementation-heavy role with real ownership. You will take a modeling approach from prototype to a shipped, monitored feature, and you will own its accuracy and latency in production.
You will build in an AI-first engineering environment - coding agents running inside a harness we own, evals gating AI-generated changes, GitHub Copilot Enterprise and Claude in the daily loop, and MCP-based tooling that lets agents reach real build, test, and telemetry systems under human-in-the-loop review. On this team that extends into the model workflow itself: agents scaffold experiments and triage dataset failures, and an accuracy regression suite gates a model change the same way a test suite gates a code change.


Your Responsibilities:

  • Implement and ship machine learning capabilities in the product, from model training pipeline through the user-facing configuration workflow.
  • Build and maintain the training, labeling, and dataset management pipelines the product and the field depend on.
  • Develop evaluation suites and accuracy regression tests that gate model changes before release.
  • Tune models and inference pipelines to meet latency and throughput targets on edge hardware.
  • Debug model behavior against real customer data and turn field failures into dataset and evaluation improvements.
  • Participate in design, code, and model reviews, and contribute to the team's ML engineering practices.

The Essentials - You Will Have:

  • Bachelor's Degree or Equivalent Years of Relevant Work Experience

The Preferred - You Might Also Have:

  • Typically requires 5+ years of related experience in a software product development environment.
  • Bachelor's or advanced degree in Computer Science, Electrical Engineering, or a related technical discipline.
  • Depth in PyTorch or TensorFlow and in modern computer vision architectures.
  • Experience with edge inference and model optimization - ONNX, TensorRT, quantization.
  • Experience building dataset and labeling pipelines, including handling class imbalance and label noise.
  • Familiarity with evaluation-driven workflows: offline metrics, regression suites, and production monitoring.
  • Exposure to industrial automation, machine vision, or manufacturing quality systems.
  • Hands-on experience building and training machine learning models in Python
  • Experience deploying a model into a production system and supporting it afterward

What We Offer:

  • Health Insurance including Medical, Dental and Vision
  • 401k
  • Paid Time off
  • Parental and Caregiver Leave
  • Flexible Work Schedule where you will work with your manager to enjoy a work schedule that can be flexible with your personal life.
  • To learn more about our benefits package, please visit at www.raquickfind.com.

This position is part of a job family. Experience will be the determining factor for position level and compensation


At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles.


For this role, the Base Salary Compensation is 114,720.00 - 172,080.00 USD Annual with an annual target bonus of 5% of base salary. Our benefits for the US can be found here. Actual pay will be based on factors such as skills, knowledge, education, and experience.


#LI-Remote

#LifeAtRok

We are an Equal Opportunity Employer including disability and veterans. 

If you are an individual with a disability and you need assistance or a reasonable accommodation during the application process, please contact our services team at +1 (844) 404-7247.

Skills Required

  • Bachelor's degree or equivalent years of relevant work experience
  • 5+ years of related experience in a software product development environment
  • Bachelor's or advanced degree in Computer Science, Electrical Engineering, or a related technical discipline
  • Experience with PyTorch or TensorFlow and modern computer vision architectures
  • Experience with edge inference and model optimization, including ONNX, TensorRT, and quantization
  • Experience building dataset and labeling pipelines, including handling class imbalance and label noise
  • Familiarity with offline metrics, regression suites, and production monitoring
  • Exposure to industrial automation, machine vision, or manufacturing quality systems
  • Hands-on experience building and training machine learning models in Python
  • Experience deploying a model into a production system and supporting it afterward

Rockwell Automation Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Rockwell Automation and has not been reviewed or approved by Rockwell Automation.

  • Healthcare Strength — Healthcare coverage is described as comprehensive, spanning medical, dental, vision, mental‑health support, disability and life insurance, and wellness resources. Multiple plan choices and supportive programs contribute to the package feeling well‑rounded.
  • Retirement Support — Retirement benefits include a 401(k)/Retirement Savings Plan with employer matching that is positioned as a meaningful part of total compensation. These offerings reinforce longer‑term financial security as a core strength.
  • Parental & Family Support — Paid parental leave was expanded and a paid caregiver leave was added, indicating clear support for family needs. These policies are complemented by flexibility signals and dedicated paid volunteer time.

Rockwell Automation Insights

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