Edge ML Engineer — Real-Time Vision (Equity)

Together for Talent; Pittsburgh (Allegheny County); On-site; USD 125,000 - 175,000; Full time

Job summary

Together for Talent is seeking a hands-on Machine Learning Engineer to own the computer‑vision models at the heart of an early-stage AI platform for real-time quality inspection. You will work with production-line imagery, build and deploy defect detection models, and optimize them for edge hardware.

The role emphasizes on-site work in Pittsburgh, PA, with 3+ years in ML engineering focused on computer vision, and strong Python/PyTorch or TensorFlow expertise.

Qualifications

• 3+ years of ML engineering with a strong computer-vision focus.
• Strong Python and PyTorch or TensorFlow experience.
• Experience training, evaluating, and deploying deep-learning models in production.
• Solid grounding in classical computer vision and image processing (OpenCV or similar).
• Familiarity with edge inference and model optimization: ONNX, TensorRT, CUDA.
• Comfortable working with messy real-world data in a startup environment.
• Willing to work on-site in Pittsburgh, PA.

Responsibilities

• Build, train, evaluate, and improve computer‑vision models for defect detection and classification
• Develop anomaly‑detection approaches for rare, changing, or poorly labeled defects
• Optimize and deploy models to edge hardware, balancing accuracy, latency, and throughput
• Work closely with hardware and embedded engineers across the inspection pipeline
• Improve data workflows: labeling, curation, augmentation, retraining, and production monitoring
• Diagnose production model issues and help establish ML tooling and best practices

Skills

Python

PyTorch

TensorFlow

Deep learning

Computer vision

OpenCV

CUDA

Latency optimization

Tools

ONNX

TensorRT

NVIDIA edge platforms

Job description

Together for Talent is seeking a hands-on Machine Learning Engineer to own the computer‑vision models at the heart of an early-stage AI platform for real-time quality inspection. You will work with production-line imagery, build and deploy defect detection models, and optimize them for edge hardware.

The role emphasizes on-site work in Pittsburgh, PA, with 3+ years in ML engineering focused on computer vision, and strong Python/PyTorch or TensorFlow expertise.