Machine Learning Engineer – Computer Vision

Rockwell Automation

. Own the modeling approach for visual inspection, including architecture selection, training strategy, and accuracy, latency, and false-reject targets .

Posted 9/22/2026full-timeRemote • United StatesSeniorLead💰 $146,880 - $220,320 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in machine learning model deployment, optimization, and evaluation, particularly in computer vision applications. Proficient in collaborating with customers and engineering teams to ensure successful model integration and performance monitoring.

Highest-signal resume keywords

Machine Learning Model DeploymentDeep Learning for Computer VisionModel Optimization TechniquesPyTorch or TensorFlowCustomer-Facing Technical Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Model Evaluation MethodologyQuantizationPruningDistillationTensorRTONNX RuntimeDataset VersioningLabeling QualityExperiment TrackingFailure-Mode Summarization

Soft Skills

MentoringTechnical Communication

Tools & Technologies

Edge DeploymentEmbedded TargetsRegression SuiteModel Monitoring

Certifications & Qualifications

Bachelor's Degree in Computer ScienceBachelor's Degree in Electrical EngineeringBachelor's Degree in Applied Mathematics

Industry Keywords

Machine Vision HardwarePLC-Based Control SystemsIndustrial EnvironmentsSoftware Product Development

Tech Stack

Tools & technologies

PyTorchTensorflow

About the role

Key responsibilities & impact

Own the modeling approach for visual inspection, including architecture selection, training strategy, and accuracy, latency, and false-reject targets
Define and maintain the evaluation methodology and regression suite that gates model releases
Version, sample, and audit labeled data
Optimize models for constrained edge targets through quantization, runtime selection, and throughput tuning
Own drift detection, retraining triggers, and production model monitoring across deployed customer installations
Partner with customers and application engineers on feasibility, data collection strategy, and acceptance criteria
Set the technical bar for the ML discipline through design review, mentoring, and written architecture guidance
Apply agents and evals to the ML workflow, including dataset triage, failure-mode summarization, and experiment scaffolding
Measure whether AI workflow improvements actually improve cycle time
Report to the Director, Software Engineering

Requirements

What you’ll need

Bachelor's Degree or equivalent years of relevant work experience
Legal authorization to work in the US is required
Will not sponsor individuals for employment visas, now or in the future, for this job opening
Typically requires 8+ years of related experience in a software product development environment
Bachelor's or advanced degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical discipline
Experience taking machine learning models from research through to production deployment
Experience with deep learning for computer vision, including detection, classification, segmentation, or anomaly detection
Experience deploying vision models to edge or embedded targets under fixed latency budgets
Depth in PyTorch or TensorFlow, and in tooling around dataset versioning, labeling quality, and experiment tracking
Experience with model optimization techniques, including quantization, pruning, distillation, TensorRT, or ONNX Runtime
Direct customer-facing technical experience: scoping applications, setting acceptance criteria, and defending a model's limits
Exposure to industrial or manufacturing environments, machine vision hardware, or PLC-based control systems
Experience building evaluation harnesses that let a team ship model changes with confidence

Benefits

Comp & perks

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
Annual target bonus of 8% of base salary