Machine Learning Engineer, Computer Vision — Hybrid/Onsite

Chooch AI; San Mateo (CA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401K with match

Paid time off

Life insurance

Job summary

Chooch AI is seeking a Machine Learning Engineer (US-based) to join a hybrid Bay Area team. You will design, train, and deploy computer vision models for healthcare, manufacturing, and retail, collaborating with customers and solutions engineers to turn requirements into measurable specs.

You will optimize models for production, monitor drift, and contribute to ML tooling while communicating clearly with both technical and non-technical stakeholders across projects.

Qualifications

• 3-5 years of industry experience building ML systems, with at least 2 years focused on computer vision.
• BS or MS in Computer Science, Electrical Engineering, Math or a related field, or equivalent practical experience.
• Strong Python and hands-on experience with PyTorch (or TensorFlow) for training and debugging deep learning models.
• Shipped at least one computer vision model to production, and can explain the trade-offs made along the way.
• Solid grasp of CNN and transformer architectures for detection, segmentation and classification.
• Experience with OpenCV and image/video processing: decoding streams, preprocessing, augmentation.
• Working knowledge of model optimization for inference (ONNX, TensorRT, quantization or similar).
• Comfortable with Docker, Git, Linux and training on GPUs in a cloud environment (AWS/Azure).
• Sound ML fundamentals: loss functions, overfitting, class imbalance, evaluation metrics and experiment design.
• Clear written and verbal communication, including explaining model behavior to non‑ML stakeholders.

Responsibilities

• Design, train and fine‑tune models for object detection, classification, segmentation, tracking and anomaly detection on real customer video and images
• Adapt pretrained and foundation models (YOLO-family detectors, ViTs, CLIP-style and vision-language models) to new customer use cases with limited labeled data
• Own data pipelines end to end: curation, labeling guidelines, augmentation, synthetic data, and dataset versioning
• Optimize models for production and edge hardware using quantization, pruning, distillation, ONNX export and TensorRT, hitting agreed latency and accuracy targets
• Build evaluation suites with clear metrics (mAP, precision/recall, false-alarm rates per camera-hour) and catch regressions before release
• Deploy and monitor models in production, diagnose drift and failure cases, and close the loop with retraining
• Work with product, solutions engineers and customers to turn vague requirements into measurable model specs
• Write clean, tested, reviewed code and contribute to shared ML tooling

Skills

Python

PyTorch

TensorFlow

CNN

Transformers

OpenCV

ONNX

TensorRT

Docker

Git

Linux

Cloud GPUs

Education

BS in Computer Science, Electrical Engineering, Math or related field

MS in related field (preferred)

Tools

OpenCV

PyTorch

TensorFlow

ONNX

TensorRT

Docker

Git

Job description

Chooch AI is seeking a Machine Learning Engineer (US-based) to join a hybrid Bay Area team. You will design, train, and deploy computer vision models for healthcare, manufacturing, and retail, collaborating with customers and solutions engineers to turn requirements into measurable specs.

You will optimize models for production, monitor drift, and contribute to ML tooling while communicating clearly with both technical and non-technical stakeholders across projects.